Has the internet ruined Human Resources? – Dr Justine Ferrer

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Welcome to Ruined by the
Internet.

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I'm Gareth King.
Today we're asking, has the

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Internet ruined human resources?
It promised to make things more

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efficient, objective and data
driven, but instead turn a human

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centric discipline into an
automated, impersonal system

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with new ethical and privacy
concerns.

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To help us explore how people
and technology work together,

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we're joined by Doctor Justine
Ferrer, a senior lecturer in

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Human Resource Management in the
Deacon Business School.

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

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show.
Thank you for having me.

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I'm, I'm very excited about
being here and having this

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discussion with you today,
Gareth.

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Yeah, me too.
But before we begin, can you

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tell us a little bit about the
work that you do and the journey

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that's LED you to this point?
Wow, the work that I do as I'm

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an academic, I work at Deakin
University in the Deakin

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Business School.
I am a senior lecturer in human

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resource management.
I have been in this space for

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quite a while and I think my
passion is around HR and the

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profession, particularly the
dark side elements.

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And and as our discussion today
will entail, some of that is

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considered the technology and
that's got its own little dark

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side that has implications for
for HR and and for the workplace

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generally.
Yeah.

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Look, I'm sure we will go into
those implications for HR in the

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workplace as we know, you know,
it's in the name.

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Human resources is obviously a
traditionally human centric

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field.
But as we look at the increased

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adoption of various forms of HR
tech, what would you say is

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proving to be the most difficult
about maintaining that human

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touch?
Really great question and a

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really hard question to to
answer because there is argument

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that you know, HR is losing its
human side because of technology

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and because of focuses on
efficiencies and productivity as

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a opposed to looking after the
well being of the employees in

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the workplace.
And if we go back historically

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to traditional models of HR, it
was about looking after that

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well being.
But HR has seen a massive shift

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and with that shift it's become
more strategic and with more

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strategic focus, it's focusing
on productivity and greater

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efficiencies.
However, when we think about HR,

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it's has two notable parts of
it.

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There is the process part.
Now HR is all about looking

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after how the workplace
functions, how employees

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function, so making sure people
are are coming to work, that

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they're getting paid, that they
have the right training and, and

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safety demands met and so on and
so forth.

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So there's a process part of
that, but there's also the human

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side of that, which as much as,
as we talk about technology and,

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and dehumanising human resource
management, there is this

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massive part of HR that is
inherently human.

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And I'm not sure that that can
be lost just yet.

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It sounds like as well that the
function of HRS expanded and

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grown quite a lot over time and
you just mentioned there that

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there has been that shift
towards a more strategic

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approach overall.
Can you just give us a top line

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rundown of what that shift has
looked like?

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It depends who you ask to be
honest.

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So what what we're seeing is and
you and you look at RE, which is

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a strange human resource
institute and even coming out of

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the US and and the UK, they're
talking about the importance of

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HR having a strategic role on
boards and making a strategic

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contribution.
So we're thinking of CEOs that

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they're making decisions that
are impacting on the whole of

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the organisation, including the
human resource, so including the

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people.
So the argument is from a

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strategic perspective that HR
should be involved in that

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conversation because ultimately
it's the employees who are going

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to deliver on those
organisational goals and those

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the objectives that they're
setting.

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So HR strategy inherently should
be linked to the business

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strategy.
So HR, when we're talking about

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HR being more strategic, it's HR
understanding what the business

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strategy is and then being able
to link their own strategy, the

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people strategy, to ensure that
the employees are delivering on

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what the organisation needs for
them to deliver on.

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In that case, have those various
forms of HR tech that have been

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implemented so far, are they
actually freeing up human

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resources staff to be more
strategic and more human?

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Or do they somewhat shift those
previous administrative burdens

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because obviously they would
need some kind of management and

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oversight from the person,
right?

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Yeah, absolutely.
So I was talking to a colleague

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recently and she was talking
about the impacts of AIM on her

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current workforce.
And she was saying that people

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are scared that they're going to
be replaced.

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You know, that this move towards
automation in, in different

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ways, whether it's through AI or
through other types of

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automation, people are going to
lose their jobs.

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And, and she's saying that or
trying to encourage them to

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think about, well, how well
should you use your time?

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How could you better use that in
order to do something that's

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more productive?
There is a case at Coles recent,

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recently, a couple of years ago
where they introduced ASAP

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SuccessFactors, which is a whole
integrated workplace system with

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lots of data and, and things
like that.

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And, and it automated quite a
lot of their HR process.

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But what they were able to do in
that was then reallocate people

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to to do things that were more
meaningful to them.

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So it wasn't about, we've got
this, you're going to be

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replaced.
It was about giving them the

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opportunity to say, all right,
well, what can you do that's

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more meaningful to the to the
business?

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How can you better spend your
time?

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And I think that that that
sentiment, I guess that that

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wider sentiment actually comes
up regarding AI in a lot of

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different things.
You know, there is obviously so

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much unknown and uncertainty
around it.

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Now.
From one side, you've got people

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thinking this is my replacement.
And then the other side, you

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know, which I'm sure we'll get
to, is people thinking, this is

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my augmentation.
This is going to make me a super

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version of myself.
So there's, you know, it's going

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to be super interesting to see
how that all shakes out.

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But you mentioned something
there around, you know, the data

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and, and inputs from various
members of staff across various

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parts of their performance and I
guess their role within the

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business, etcetera.
Obviously, people have a little

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bit wary of being treated as
data.

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Is there a risk that the
employees will feel like they're

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just being reduced to a series
of data points and metrics

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rather than the human beings
that they are?

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And does something like that
potentially get worse by

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necessity, simply because the
larger an organisation gets, the

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harder the task of managing all
the staff is?

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Yeah, So absolutely the
dehumanisation and the

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reductionism that comes with
people thinking they've just

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been reduced to a number and and
the consequential impacts of

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that for employee well being a
substantial you know, it, it

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it's, but I think it's a more of
a cultural discussion as an

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organisation as to why we're
doing this, why we need to do

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this, why this is important and
where those touch points are for

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human engagement and human
interaction.

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And, and we see this a lot,
Gareth, now with working from

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home, where, where are those,
where are those emotional touch

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points that you have with
someone where we just can sort

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of gas bag and, and say
whatever, it's the same in this

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translation or the use of metro
tricks to drive a lot of our

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decision making and, and a lot
of what happens in organisation.

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And you're right, data has
become a commodity now and

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substantially more and more
we're seeing it.

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I was reading a study recently
about applicants applying for

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jobs and, and they were faced
with automation the entire way

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through.
They didn't actually engage with

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a person, a human until the
very, very end.

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And it's like, well, what is the
consequence for that, for

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building your employer brand,
for your how you feel about the

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organisation?
So there is, there is a big

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story around that.
And I don't think we've really

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started to unpack what that
looks like.

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But there definitely is that
reductionism that people being

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reduced to a number and and also
the idea that humans are complex

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individuals and can they be
reduced to a number or should

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they be reduced to a number is
also the big question there.

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Yeah, absolutely.
And I think that part of

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everything that you've you've
explained there in my mind, I

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can put a lot of it back to the
kind of unknown.

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And you said something there
around managing your employer

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brand.
If the impression that you're

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giving is your, you've automated
everything and you've got all

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these applicants applying for a
role or an interest in your

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company being faced with these
automated systems that don't

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treat them like that human,
regardless if you're doing it

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out of necessity, like that
almost doesn't really matter to

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that person on the outside.
They only know what they're

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faced with.
So yeah, they're it'll be really

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interesting to see how that all
falls out around how people

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manage their employer brand.
But you, you also mentioned

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there around work from home.
One thing that I've seen and,

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and read a little bit of
recently was the implementation

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of surveillance tools from, you
know, organisations of various

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types, whether they're kind of
keystroke loggers or you know, I

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was reading something earlier
today around some company

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activated some software that
recorded through the microphones

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their their Staffs computers
while they're at home working

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from home.
So there's obviously all these,

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you know, in my mind, quite
dodgy things going on and I can

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only guess that that adds to
that cynicism and that distrust

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amongst workers who feel like
they're being monitored due to

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these various tech solutions.
That said, if that perceptions

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out there, what are the
implications of that for

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workplace culture?
How would that be addressed?

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You know, the more tools to try
and spend more time working on

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culture feels like is what's
breaking that cultural

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perception in the 1st.
Place Well, well, yeah, I think

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with surveillance and when we
talk about surveillance tools,

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we automatically go to the
negative surveillance, you know

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that I'm sneaking around as an
employer and I'm checking up on

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you.
Now we know through COVID there

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was a substantial increase in
organisations accessing those

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surveillance tools that they
were using online.

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But we also surveil people in
with cameras in the workplace.

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We can also surveil them by
require them to do drug tests,

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you know, So there's a whole
range of different surveillance

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that we do in organisations.
And you know, it's often sold to

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us as surveillance as care or is
it surveillance as coercion,

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right.
You know, so this is where it,

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it, it becomes quite interesting
to me to be honest, because this

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is how it's sold to someone is
how it's implicated into the

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culture.
Yeah, that's, that's really

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interesting what you said.
There's surveillance as care.

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I can imagine you could sell
that a lot easier if it was,

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say, cameras looking over the
open plan office type thing, you

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know, versus telling someone
that you're going to be logging

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their keystrokes and microphone
in the privacy of their own

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home, you know?
And there's also surveillance

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with health monitoring where
they want you to wear a device

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to check, Oh, really?
So your, your, your blood

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pressure's not going up.
I know that.

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I think that there was, and I'm
not 100% sure on this example,

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there was a factory in China
where they were using some

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surveillance technology to sort
of check people's using facial

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recognition to see if that would
come extra and then being able

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to take them off the line and,
and, and replace them with

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someone else.
So they were using it for good.

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But were they though?
Because then you go on the other

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extreme for those people in a
call centre and they have to log

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every time they go to the
bathroom and, and how many

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minutes you, you've got like 3
1/2 minutes to go to the

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bathroom.
And you can't only have so many

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bathroom breaks.
So it's it's problematic.

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Yeah, look, you know, we've all
heard stories around, you know,

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Amazon, how they're managing
their warehouse stuff.

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That's just one, one example off
the top of my head.

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And that sounds absolutely not
surveillance as care.

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That's why surveillance as as
crushing of the soul.

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But we've we've also looked at
the amount of data that is being

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collected potentially on on
people within and outside the

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workplace.
What are the biggest challenges

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and risks that human resources
departments face when collecting

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and analysing so much of this
data?

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The probably the biggest one is
privacy and you know, that's not

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just AHL problem, that's an
organisational wide problem and

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just ensuring that the, the
employee data we're talking

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about data is, is safe and, and
it's protected by the firewalls

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and whatever that whatever the
organisation has to protect it.

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However, we do know that there
can be breaches and those

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breaches may be unintentional or
they may be intentional or it

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might be a third party breach.
So it's it's about then the

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organisation being on top of and
ensuring that they've got the

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systems in place to protect the
data.

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Me personally, I've, I've been
in a couple of those breaches so

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far, like, you know, whereas
various things have been hacked

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00:13:14,160 --> 00:13:15,760
and it's like, oh, your licence
is gone.

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I was like, oh, awesome.
But with, with those concerns

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around privacy, how do you, I
mean, how do organisations

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beyond saying that they, it's
stored well and you know, you

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see that little padlock in the
in the browser thing when you're

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handing over your stuff, like
how do they manage it securely

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enough to build the trust from
employees and beyond?

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I think it comes back to
communication and, and that

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cultural piece to say that we
have invested X or we have

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invested in this company to do
this and their reputation

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00:13:48,080 --> 00:13:50,640
exceeds them in this particular
space.

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Or we have the big banks, they,
they hire those hackers and they

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set up the, whoever hacks, it
gets $20,000, you know, and, and

258
00:14:00,120 --> 00:14:03,600
it goes out to the hackers to
hack a particular system, you

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know, so they're, they're
actively doing things.

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And I know some companies are
hiring hackers to have in their,

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in their company to be hacking
everything so that they, they

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can identify where some of those
pitfalls are and where those

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00:14:17,360 --> 00:14:21,640
sort of back entries might be or
whether be able to sort of get

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in.
But it does come down to

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communication.
Let's go back to some of the

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reasons why HR is starting to
implement various forms of

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technology for efficiency and
the scale of of what they're up

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against.
I often, you know, see this

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00:14:38,000 --> 00:14:41,680
digital deluge that HR
departments currently face.

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00:14:42,000 --> 00:14:45,800
Most often from what I've seen,
that refers to say you put a job

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advert out in the world
previously, I don't know, you

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00:14:48,960 --> 00:14:52,240
might have got 50 applicants,
now you're getting 800.

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00:14:52,680 --> 00:14:56,680
And obviously that's just a
ridiculous amount for somebody

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to try and sort through
themselves, which which makes

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those tools such a necessity.
If you've got these gigantic

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00:15:04,240 --> 00:15:07,600
corporates, right, let's say
they're probably most likely to

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be using these systems in the
name of efficiency and, and

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00:15:11,280 --> 00:15:14,520
managing that scale.
But when it comes to smaller

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00:15:14,680 --> 00:15:19,840
businesses, do they have an
advantage to potentially being

280
00:15:19,840 --> 00:15:22,800
behind the cutting edge when it
comes to these tools?

281
00:15:23,320 --> 00:15:25,440
And, you know, is there an
advantage there in, in

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00:15:25,440 --> 00:15:28,760
maintaining some of that human
face and touch?

283
00:15:28,920 --> 00:15:32,240
I, I, I think it's a, almost a
double edged sword, Gareth, for

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00:15:32,240 --> 00:15:35,640
small businesses, they can't
afford to invest in the

285
00:15:35,640 --> 00:15:38,360
technologies that the big
companies are using.

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00:15:38,360 --> 00:15:39,960
So that that's one of the big
things.

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00:15:39,960 --> 00:15:44,280
So their reliance will be on, on
different types of systems.

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00:15:44,400 --> 00:15:46,840
So they still have some data and
they'll still be collecting it,

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00:15:46,840 --> 00:15:50,200
but how they go about collecting
it is is might be quite

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00:15:50,200 --> 00:15:53,920
different to a big organisation.
However, as you say, it does

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00:15:53,920 --> 00:15:57,520
allow them to be more human, but
they have more hands on that

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00:15:57,520 --> 00:15:59,400
they have to be more involved
in.

293
00:15:59,680 --> 00:16:02,080
Now.
I'm not sure if you know any,

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00:16:02,360 --> 00:16:07,560
any HR people that are working
in a small firm where there's

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00:16:07,560 --> 00:16:11,160
like one or two of them now, I'm
sure they're wishing that they

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00:16:11,160 --> 00:16:15,000
had more automation because they
don't have enough time even to

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00:16:15,000 --> 00:16:17,840
be human because they're going
jumping from one ship to the

298
00:16:17,840 --> 00:16:19,920
next.
They're going from a performance

299
00:16:19,920 --> 00:16:23,600
review to a workplace dispute to
some other, like they're jumping

300
00:16:23,600 --> 00:16:26,800
around.
So for them, I think using tools

301
00:16:26,800 --> 00:16:29,680
to streamline position
descriptions or something like

302
00:16:29,680 --> 00:16:33,480
that to take some of that menial
stuff out of it for them.

303
00:16:33,480 --> 00:16:36,400
So then they potentially have a
little bit more time.

304
00:16:36,640 --> 00:16:38,760
Yeah, yeah.
And I think you've, you've kind

305
00:16:38,760 --> 00:16:42,320
of outlaid a few things there,
which a lot of the time when

306
00:16:42,320 --> 00:16:47,240
people hear human resources like
their, their mind goes to this

307
00:16:47,240 --> 00:16:49,280
is kind of the gatekeeper of a
job.

308
00:16:49,640 --> 00:16:53,520
Do you know what I mean?
But the role of HR departments

309
00:16:53,520 --> 00:16:56,840
is so much wider than that, as
you've kind of just touched on

310
00:16:56,840 --> 00:16:58,680
right now.
Can you just give us a bit of a

311
00:16:58,680 --> 00:17:01,840
rundown of the wider world of
HR, what it looks like

312
00:17:01,840 --> 00:17:03,880
currently?
Well, going back to an early

313
00:17:03,880 --> 00:17:06,960
point I made about that process
versus the human side.

314
00:17:06,960 --> 00:17:09,720
Now when we talk about the
process side that's around

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00:17:09,720 --> 00:17:13,800
payroll, that's around things to
get, you want holiday pay.

316
00:17:14,040 --> 00:17:17,000
It's it's in the system like
getting all those systematic

317
00:17:17,000 --> 00:17:20,040
things that can be automated,
automated like there's a lot of

318
00:17:20,040 --> 00:17:22,640
processes that we have to follow
if it's about policy

319
00:17:22,640 --> 00:17:25,160
development.
But then the human element is

320
00:17:25,160 --> 00:17:27,040
the other part of it.
And that's where we're having

321
00:17:27,040 --> 00:17:30,960
conversations might be dealing
with a dispute or workplace

322
00:17:30,960 --> 00:17:33,560
investigation.
It might be performed management

323
00:17:33,560 --> 00:17:35,800
conversations.
Now performance management is a

324
00:17:35,800 --> 00:17:40,520
tricky one because some of it
may be automated or using a tech

325
00:17:40,800 --> 00:17:44,280
to you go in the system, you
fill in your goals, that type of

326
00:17:44,280 --> 00:17:46,720
thing.
But then it's usually, I say

327
00:17:46,720 --> 00:17:49,160
usually loosely, I'd like to
think everyone does it.

328
00:17:49,360 --> 00:17:50,960
There is a human discussion with
that.

329
00:17:50,960 --> 00:17:53,920
There's human touch points where
we sort of say, how is it

330
00:17:53,920 --> 00:17:58,440
actually really going?
And and that's critical to

331
00:17:58,480 --> 00:18:01,560
ensure that the employees are
finding meaning in what they're

332
00:18:01,560 --> 00:18:03,560
doing.
So I can go in and fill it, but

333
00:18:03,560 --> 00:18:07,280
if no one's looking at it or no
one cares, then how, how is that

334
00:18:07,280 --> 00:18:10,040
meaningful for me?
And that, you know, leads onto

335
00:18:10,040 --> 00:18:13,040
all other things like low job
satisfaction, low commitment,

336
00:18:13,040 --> 00:18:14,880
engagement, productivity, and so
on.

337
00:18:15,600 --> 00:18:18,800
Yeah, look, it, it sounds like
as you said earlier too, that

338
00:18:18,800 --> 00:18:23,120
that human aspect still needs to
be so strong in everything

339
00:18:23,120 --> 00:18:26,840
because humans as, as we all
know, they're not machines like

340
00:18:26,840 --> 00:18:31,880
the incredibly complicated
beings with absolutely unique

341
00:18:31,880 --> 00:18:36,040
sets of needs and wants.
But while we are talking around

342
00:18:36,280 --> 00:18:40,280
AI and and these new tools, this
is like quite a big, huge

343
00:18:40,280 --> 00:18:42,840
discussion that with a lot of
areas that this can go.

344
00:18:43,760 --> 00:18:47,960
One of the things that I guess
is out in the discourse is

345
00:18:47,960 --> 00:18:53,600
around AI and bias in hiring and
management of teams and and

346
00:18:53,600 --> 00:18:55,400
people.
Some people say it helps

347
00:18:55,400 --> 00:18:59,360
eliminate these biases, but
others say introduces new even

348
00:18:59,360 --> 00:19:02,200
harder to spot ones.
What's your take on this?

349
00:19:02,320 --> 00:19:05,240
Yeah.
Well, just taking a step back to

350
00:19:05,560 --> 00:19:09,800
algorithms and algorithmic bias
just in the data, I think that's

351
00:19:09,800 --> 00:19:15,280
a, a part of this discussion
before AI even was part of the

352
00:19:15,520 --> 00:19:19,480
bias discussion because it's not
operating in isolation.

353
00:19:19,480 --> 00:19:22,920
Whether it's an algorithm or or
whether it's an AI, someone's

354
00:19:22,920 --> 00:19:25,960
inputting something.
Yes, it has the ability to

355
00:19:26,000 --> 00:19:28,840
address bias, but it depends
what's going into it at the

356
00:19:28,840 --> 00:19:31,120
start.
Now we can't make assumptions

357
00:19:31,400 --> 00:19:36,560
that the information and the
positioning that's putting it at

358
00:19:36,560 --> 00:19:40,080
the start is completely without
bias because bias is going to

359
00:19:40,080 --> 00:19:43,120
be, whether it's unconscious
bias or not, it's going to be

360
00:19:43,120 --> 00:19:46,360
inherent in in everything and as
well as errors.

361
00:19:46,760 --> 00:19:50,560
So it has the ability to address
so many things, including bias.

362
00:19:51,160 --> 00:19:54,280
However, from HR perspective,
they just have to be wary and

363
00:19:54,280 --> 00:19:58,280
questioning and checking because
the biggest problem I think with

364
00:19:58,400 --> 00:20:01,920
a lot of HR systems and
particularly HR tech is a set

365
00:20:01,920 --> 00:20:06,200
and forget mentality where it's
like I said it, I do it here is

366
00:20:06,200 --> 00:20:09,760
a process irrespective of what
it is, and then I forget about

367
00:20:09,760 --> 00:20:11,040
it.
Well, it's like, well, knowing

368
00:20:11,040 --> 00:20:13,360
actual fact is an evaluative
part of that.

369
00:20:13,360 --> 00:20:16,640
We have to go back, check is
what's coming out, the writing.

370
00:20:16,760 --> 00:20:19,400
Information, do we need to go
back and check what's going in

371
00:20:19,560 --> 00:20:22,680
or what we're saying or we're
asking the AI to do for us?

372
00:20:22,680 --> 00:20:26,960
So yes, is there new biases
coming out potentially?

373
00:20:27,200 --> 00:20:29,240
I I don't know, it's a scary
thought.

374
00:20:29,600 --> 00:20:32,320
You said something there around,
you know, you've still got to

375
00:20:32,320 --> 00:20:35,600
have someone go in and kind of
mine through the data and find

376
00:20:35,600 --> 00:20:38,280
the right outputs and and
summarise what is presenting

377
00:20:38,280 --> 00:20:41,720
what it's finding is that quite
a big skill for people to learn

378
00:20:41,720 --> 00:20:46,040
And does that present a new
problem, which if there is that

379
00:20:46,040 --> 00:20:48,280
learning curve to analysing that
stuff?

380
00:20:48,280 --> 00:20:50,040
I mean, look, I don't know how
complicated it is.

381
00:20:50,040 --> 00:20:52,160
I struggle to look in Google
Analytics.

382
00:20:52,160 --> 00:20:53,640
That's that's how bad I am at
it.

383
00:20:53,960 --> 00:20:56,880
But if, if people are using
these tools to process all this

384
00:20:56,880 --> 00:20:59,960
data and then they've got to
spend all this time looking at

385
00:20:59,960 --> 00:21:02,280
it and and finding the
conclusions that are reaching

386
00:21:02,280 --> 00:21:04,720
and out putting something.
Is there a risk that people

387
00:21:04,720 --> 00:21:08,680
could become too reliant on tech
to solve all of these problems,

388
00:21:09,400 --> 00:21:11,880
whether they're forced to or
whether they choose to?

389
00:21:12,480 --> 00:21:16,000
I think there is an potential
that people will become too

390
00:21:16,000 --> 00:21:20,160
reliant on it because if I don't
understand what's coming out of

391
00:21:20,160 --> 00:21:24,400
it, then how do I know if what's
coming out is wrong or right or

392
00:21:24,720 --> 00:21:28,720
correct or biassed or you know,
So there is a certain level of

393
00:21:28,720 --> 00:21:31,920
skill required just to
understand the data.

394
00:21:32,240 --> 00:21:35,360
And we're, we're seeing more
sophisticated HR systems now

395
00:21:35,360 --> 00:21:38,440
where all the data is in the
back end and you can go in and

396
00:21:38,440 --> 00:21:41,720
you can ask it.
Tell me about the turnover

397
00:21:41,720 --> 00:21:45,440
trends for the the next and it
will spit out the data and give

398
00:21:45,440 --> 00:21:48,640
you and answer the question.
But then the problem becomes

399
00:21:48,760 --> 00:21:53,400
couple problems. 1 is a data
correct. 1 error in a line of

400
00:21:53,400 --> 00:21:57,200
code can, can break it all and,
and we don't know unless

401
00:21:57,200 --> 00:22:00,360
someone's checking it.
And two, how do I know what

402
00:22:00,360 --> 00:22:03,920
questions to ask?
So, so we, we hear a lot about,

403
00:22:04,040 --> 00:22:07,680
you know, ChatGPT and, and all
those generative AIS and, and

404
00:22:07,760 --> 00:22:10,320
the importance of how, how we
write prompts.

405
00:22:10,360 --> 00:22:12,680
It's going, it's going to be the
same thing for this.

406
00:22:12,800 --> 00:22:16,320
It's about what type of
questions do we need to ask the

407
00:22:16,320 --> 00:22:20,040
AI in order to draw out what we
need from an organisational

408
00:22:20,040 --> 00:22:22,480
perspective.
But the other at the other end

409
00:22:22,480 --> 00:22:25,920
of that or the other start of
that is have we collected the

410
00:22:25,920 --> 00:22:28,280
right data in the first place?
Yeah.

411
00:22:28,720 --> 00:22:31,680
But then be able to get the
right information out of it.

412
00:22:31,680 --> 00:22:35,480
So yes, there is an opportunity
to become over reliant.

413
00:22:35,760 --> 00:22:39,280
Secondly, the skills required
are analytical skills.

414
00:22:39,360 --> 00:22:43,600
And even when I talk to
different people in in HR, HR

415
00:22:43,600 --> 00:22:46,480
managers, they're looking for
particular analytical skills for

416
00:22:46,480 --> 00:22:49,680
new people coming in, people who
can analyse some data, who can

417
00:22:49,680 --> 00:22:54,080
read it and can interpret it and
make then use it to make data

418
00:22:54,080 --> 00:22:56,520
driven decisions.
That makes total sense.

419
00:22:56,760 --> 00:22:59,160
There's two things I want to
explore from that What other new

420
00:22:59,160 --> 00:23:01,920
skills do people in the field
need to learn?

421
00:23:02,600 --> 00:23:06,320
And then also, does it still
come down to humans to predict

422
00:23:06,840 --> 00:23:09,000
where and how those trends might
continue?

423
00:23:09,200 --> 00:23:13,320
OK, the new skills, absolutely
analytical skills that prompt

424
00:23:13,320 --> 00:23:16,480
into engineering like that,
getting the right prompts,

425
00:23:16,480 --> 00:23:19,480
critical thinking skills, I
think it's always been on the

426
00:23:19,720 --> 00:23:23,120
cards pretty much for everyone,
but for HR particularly to all

427
00:23:23,120 --> 00:23:26,760
right, how can I, how can I look
at this in a different way, not

428
00:23:26,760 --> 00:23:29,400
just take for granted what's
being spit out.

429
00:23:30,040 --> 00:23:32,720
So just a little bit of those
broader type of skills.

430
00:23:32,840 --> 00:23:37,400
We are seeing increasingly more
sophisticated autonomous

431
00:23:37,440 --> 00:23:42,560
programmes that can actually
tell you like the trend or or

432
00:23:42,560 --> 00:23:46,160
give you the actual answer.
So I don't know if I answered

433
00:23:46,160 --> 00:23:47,560
your second question quite
right.

434
00:23:47,560 --> 00:23:50,440
No, no, I think, I think that
actually could lead us into

435
00:23:50,440 --> 00:23:53,800
another question, which is
around those tools as they get

436
00:23:53,800 --> 00:23:56,560
more autonomous.
When I've played this entire

437
00:23:56,560 --> 00:24:00,360
scenario out in my own mind, the
best case scenario I can imagine

438
00:24:00,360 --> 00:24:02,760
is everything's get so
autonomous that it's just kind

439
00:24:02,760 --> 00:24:05,720
of human to human conversations
again, and all the

440
00:24:05,720 --> 00:24:08,960
administrative data driven stuff
is just running in the

441
00:24:08,960 --> 00:24:12,040
background.
Is there that that potential or

442
00:24:12,040 --> 00:24:17,640
does that full autonomy over so
much of it kind of tap into

443
00:24:17,840 --> 00:24:20,840
everybody's worst fear around
AI, which is kind of it's a

444
00:24:20,840 --> 00:24:23,880
human replacer?
It depends if who you're

445
00:24:23,880 --> 00:24:26,760
reading, because that everyone's
got a real different view on

446
00:24:26,760 --> 00:24:29,040
this.
Like I know Elon Musk has has

447
00:24:29,040 --> 00:24:31,320
come out and said AI is going to
be fully developed and

448
00:24:31,320 --> 00:24:33,520
autonomous in, in this
particular year.

449
00:24:33,680 --> 00:24:36,160
And then others are saying,
well, we've pretty much hit the

450
00:24:36,440 --> 00:24:38,680
the top of where we'll hit and
we'll sort of stagnate for a

451
00:24:38,680 --> 00:24:41,160
little bit at where we are.
I get the point.

452
00:24:41,160 --> 00:24:42,920
Are we being replaced by the
machine?

453
00:24:43,720 --> 00:24:47,720
And, and this is the the biggest
question and I think for HR this

454
00:24:47,720 --> 00:24:51,000
is absolutely significant
because HR as a function in the

455
00:24:51,000 --> 00:24:54,040
organisation was probably the
first adopters to start

456
00:24:54,120 --> 00:24:56,160
implementing different types of
technology.

457
00:24:56,160 --> 00:25:00,040
And then seeing the value of
what AI can actually provide.

458
00:25:00,120 --> 00:25:03,080
It's like, well, is it going to
replace us?

459
00:25:03,120 --> 00:25:09,080
Are we going to lose our jobs?
It is scary to know when it's

460
00:25:09,080 --> 00:25:12,280
going to where it can go.
But one of those topics that

461
00:25:12,280 --> 00:25:15,440
have just come up there is AI
and HR decisions just in

462
00:25:15,440 --> 00:25:19,600
general, as businesses face
increasing scrutiny and calls

463
00:25:19,600 --> 00:25:23,320
for regulation across this
stuff, what procedures and

464
00:25:23,320 --> 00:25:28,080
protocols either are they or
might they potentially implement

465
00:25:28,080 --> 00:25:30,160
to address this?
I think they just have to have a

466
00:25:30,160 --> 00:25:33,520
clear framework, maybe an
ethical framework, I'm not sure,

467
00:25:33,520 --> 00:25:36,680
just to say what what as an
organisation we're going to

468
00:25:36,680 --> 00:25:40,640
tolerate and what we won't, how
we can use it and how we can't.

469
00:25:41,040 --> 00:25:44,400
Until we get some national
standards about how it's used or

470
00:25:44,400 --> 00:25:46,800
how we can use it.
It's really hard for

471
00:25:46,800 --> 00:25:51,640
organisations to know what the
general consensus is.

472
00:25:51,800 --> 00:25:54,960
So I think then if we are
talking regulation, something

473
00:25:54,960 --> 00:26:00,560
I've seen lately is these
current US legal cases around, I

474
00:26:00,560 --> 00:26:03,640
think it was one guy has
launched some and I, what do

475
00:26:03,640 --> 00:26:06,520
they call it like a suit or, or
something over there because he

476
00:26:06,520 --> 00:26:09,480
got rejected by AI from, I don't
know, let's say a couple of 100

477
00:26:09,720 --> 00:26:13,000
rolls and he thinks it's shit.
But it might be, it might not

478
00:26:13,000 --> 00:26:16,640
be, but it doesn't matter.
Do cases like this kind of set a

479
00:26:16,640 --> 00:26:18,520
precedent?
Who gets a final word in

480
00:26:18,520 --> 00:26:20,840
something like that?
And depending on the outcome of

481
00:26:20,840 --> 00:26:24,160
that case, how could it
potentially change how these

482
00:26:24,160 --> 00:26:26,920
systems are used by all
companies moving forward?

483
00:26:27,360 --> 00:26:28,880
Well, that case is really
interesting.

484
00:26:28,880 --> 00:26:31,480
So he's suing work day work.
Day.

485
00:26:31,520 --> 00:26:33,680
That's the.
One to say that work day has

486
00:26:33,680 --> 00:26:36,560
discriminated against him
because of his age and has

487
00:26:36,560 --> 00:26:40,120
stopped him even getting through
to interview stage on on any of

488
00:26:40,120 --> 00:26:43,920
it based on the algorithm or the
AI that they've used.

489
00:26:43,920 --> 00:26:48,960
And in reading the cases, it's
really quite interesting in who

490
00:26:48,960 --> 00:26:51,560
has that owners of
responsibilities, the employing

491
00:26:51,560 --> 00:26:55,000
organisation, or is it the
company who has the technology,

492
00:26:55,160 --> 00:26:57,800
who's selling the technology?
And that's who he was.

493
00:26:57,800 --> 00:27:01,360
He was suing the technology
company to say that all the

494
00:27:01,360 --> 00:27:05,360
organisations I went to that
used your technology were

495
00:27:05,360 --> 00:27:06,840
discriminating against me, I
think.

496
00:27:06,880 --> 00:27:09,960
I'm think that's what I read.
No, that that sounds about right

497
00:27:10,040 --> 00:27:11,520
from what I've taken from the
case.

498
00:27:11,520 --> 00:27:13,840
But that, you know, that brings
back an interesting parallel.

499
00:27:13,840 --> 00:27:17,120
What like if someone commits a
crime through the Internet, you

500
00:27:17,120 --> 00:27:19,760
know, who's to blame?
Is it the person?

501
00:27:19,760 --> 00:27:21,760
Is it the Internet service
provider?

502
00:27:21,960 --> 00:27:24,480
It's it's just kind of like
where does the finger point at

503
00:27:24,480 --> 00:27:26,280
the end of the day for the
blame?

504
00:27:26,280 --> 00:27:29,840
But you know a system like like
that, surely the companies have

505
00:27:29,840 --> 00:27:33,920
some control over what you know,
selections and inputs that they

506
00:27:34,200 --> 00:27:37,040
want it to philtre, right?
But you would think so because

507
00:27:37,040 --> 00:27:40,600
that's what we have been
programmed to think in terms of.

508
00:27:40,880 --> 00:27:45,840
All right, I'm I'm buying an off
the shelf or a bespoke programme

509
00:27:46,040 --> 00:27:48,960
to help me with my recruitment
as as a company.

510
00:27:49,000 --> 00:27:52,840
I need to tell that programme
what it is I want as a company,

511
00:27:52,840 --> 00:27:55,760
what I'm looking for, what our
parameters are.

512
00:27:55,840 --> 00:27:59,320
I'm inputting that before the
system actually does the work it

513
00:27:59,320 --> 00:28:00,880
needs to do.
Yeah, no, totally.

514
00:28:00,880 --> 00:28:04,600
So I mean, it feels pretty open
and shut to me, but I, I don't

515
00:28:04,600 --> 00:28:07,600
know, I don't know how the the
US legal system will, will shake

516
00:28:07,600 --> 00:28:09,960
something like that out.
But you mentioned there there's

517
00:28:09,960 --> 00:28:13,880
still a person providing the
inputs and I guess the framework

518
00:28:13,880 --> 00:28:16,240
that can be built into that
bespoke tool.

519
00:28:16,320 --> 00:28:18,920
This, this is AI.
Don't know, it could be a bit a

520
00:28:18,920 --> 00:28:21,720
bit of a heavy question, but do
you believe AI can eventually

521
00:28:21,720 --> 00:28:26,040
make the human in human
resources obsolete or does it

522
00:28:26,040 --> 00:28:29,400
force the field to become even
more human centric in the years

523
00:28:29,400 --> 00:28:31,200
to come?
Well, that is a very heavy

524
00:28:31,200 --> 00:28:34,920
question.
But my answer to that is that I

525
00:28:34,920 --> 00:28:37,480
don't think the human will
become obsolete.

526
00:28:38,320 --> 00:28:42,840
I, I think it, there may be more
opportunity to automate and to

527
00:28:42,840 --> 00:28:45,360
use tech for some of the
processes.

528
00:28:45,680 --> 00:28:48,960
But as I mentioned before, there
is still a huge part of HR that

529
00:28:48,960 --> 00:28:53,600
is around people and, and it is
around ensuring that you know

530
00:28:53,760 --> 00:28:57,240
that the people have got the,
the capacity and the

531
00:28:57,240 --> 00:28:59,960
capabilities to do so.
It might be around, even though

532
00:28:59,960 --> 00:29:02,720
we can news tech for learning
and development, but it might be

533
00:29:02,720 --> 00:29:05,600
a career conversation or it
might be, as I said, a

534
00:29:05,600 --> 00:29:08,480
performance conversation, or it
might be I'm negotiating an

535
00:29:08,480 --> 00:29:11,840
enterprise agreement.
You know, I'm working with the

536
00:29:11,840 --> 00:29:14,040
unions.
I, you know, so they're still

537
00:29:14,240 --> 00:29:17,880
going to have to be a human part
of what HR does.

538
00:29:17,880 --> 00:29:21,640
I don't think that that's lost.
And that that makes absolute

539
00:29:21,640 --> 00:29:23,840
sense.
And hopefully that efficiency

540
00:29:23,840 --> 00:29:29,040
gain will lead to that kind of
personal interaction, human

541
00:29:29,040 --> 00:29:34,120
gain, which I guess is is what
everybody really wants to avoid

542
00:29:34,120 --> 00:29:36,480
feeling like you're just one of
those data points that we

543
00:29:36,480 --> 00:29:38,760
mentioned earlier.
So the more humanisation.

544
00:29:39,360 --> 00:29:42,440
Yeah, yeah, more humanisation.
That's a, that's a great way to

545
00:29:42,440 --> 00:29:45,200
describe what we want from human
resources.

546
00:29:45,200 --> 00:29:48,640
But just to finish up, how do
you see the future for human

547
00:29:48,640 --> 00:29:50,680
resources professionals taking
shape?

548
00:29:51,480 --> 00:29:54,640
Do you think the field will
become more human like we're

549
00:29:54,640 --> 00:29:57,920
hypothesising now, or will it
potentially end up more

550
00:29:57,920 --> 00:30:03,560
technical as we move forward?
Well, I, I would like to say it

551
00:30:03,560 --> 00:30:08,000
would become more human in the
sense that the thing with HR and

552
00:30:08,000 --> 00:30:10,600
tech and HR tech, it's a real
balancing act.

553
00:30:10,800 --> 00:30:14,160
It's a balancing act between
embracing technology and

554
00:30:14,160 --> 00:30:19,040
preserving our human values.
So HR has got this critical role

555
00:30:19,040 --> 00:30:23,240
in, in being able to do this.
So I think in an ideal world, if

556
00:30:23,440 --> 00:30:26,800
HR can do that, well, embrace
the tech, bring it along.

557
00:30:26,920 --> 00:30:30,480
We use it, we automate
processes, we we get everything

558
00:30:30,480 --> 00:30:34,920
happening then will allow us to
free our time as HR

559
00:30:34,920 --> 00:30:39,480
practitioners to then be more
human in the sense that I can be

560
00:30:39,480 --> 00:30:43,480
more interactive and engage with
the workforce and whatever that

561
00:30:43,480 --> 00:30:46,080
may mean.
Do I think it's going to happen

562
00:30:46,280 --> 00:30:49,680
in that ideal world?
Maybe for some, but I think that

563
00:30:49,840 --> 00:30:53,560
for some companies and maybe an
over reliance on technology and

564
00:30:53,560 --> 00:30:57,040
then say well, we don't need you
or we can do something else for

565
00:30:57,040 --> 00:31:00,840
you or we're going to find
something else for you to do as

566
00:31:00,840 --> 00:31:05,880
opposed to just here is an
opportunity to rehumanise HR.

567
00:31:05,880 --> 00:31:09,080
Yeah, fingers crossed that it
does rehumours.

568
00:31:09,080 --> 00:31:11,160
I really like that.
I like the way you've summed

569
00:31:11,160 --> 00:31:14,800
that up there.
Unfortunately for anybody in HR,

570
00:31:14,800 --> 00:31:18,320
it's like they're right in the
firing line now from everybody,

571
00:31:18,320 --> 00:31:20,240
whether that's external or
internal.

572
00:31:20,240 --> 00:31:23,840
So that was why I really was was
keen to hear the thoughts for

573
00:31:23,840 --> 00:31:25,960
this conversation.
Can I just add one more point

574
00:31:25,960 --> 00:31:30,800
whilst I'm, I'm, I'm presenting
this sort of almost sceptical

575
00:31:30,800 --> 00:31:34,800
view of, of technology, I do
think it has its place.

576
00:31:35,080 --> 00:31:38,120
And the HR practitioners that
I've been talking to, they're

577
00:31:38,120 --> 00:31:41,160
excited by the opportunities
that the technology is

578
00:31:41,160 --> 00:31:43,800
providing.
They're not scared of what comes

579
00:31:43,800 --> 00:31:46,160
next.
They're excited and ready to

580
00:31:46,160 --> 00:31:50,560
embrace that next stage of of
whatever it is, whatever the

581
00:31:50,560 --> 00:31:53,600
workforce is going to look like.
Interesting to hear that they're

582
00:31:53,600 --> 00:31:56,000
almost at the coalface, and if
they're feeling positive,

583
00:31:56,000 --> 00:31:59,440
hopefully that will eventually
become the feeling for everybody

584
00:31:59,520 --> 00:32:02,520
else outside the world of human
resources.

585
00:32:02,920 --> 00:32:06,200
Thanks so much for for that.
Justine, what's on the horizon

586
00:32:06,200 --> 00:32:08,680
for you and where can people
follow what you're up to?

587
00:32:09,040 --> 00:32:13,920
They can follow me on LinkedIn,
just Justine Farah and find me

588
00:32:13,920 --> 00:32:16,120
there.
I'm doing lots of things there,

589
00:32:16,200 --> 00:32:18,920
as you'll see with some
publications and the like.

590
00:32:19,120 --> 00:32:21,080
Awesome.
Justine, thank you so much.

591
00:32:21,240 --> 00:32:24,640
Thanks Gareth, I appreciate it.
For more info on what we've

592
00:32:24,640 --> 00:32:26,400
discussed today, check out the
show notes.

593
00:32:26,480 --> 00:32:28,960
If you enjoyed this one, you can
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594
00:32:28,960 --> 00:32:31,560
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595
00:32:31,560 --> 00:32:33,880
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596
00:32:34,240 --> 00:32:35,960
I'm Gareth King, see you next
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