Latest / Edan Haddock - Total Talent / Can You Still Trust a CV? Hiring in the Age of AI and Candidate Fraud

Transcript

Can You Still Trust a CV? Hiring in the Age of AI and Candidate Fraud · Edan Haddock - Total Talent

0:51
SPEAKER_01: Welcome back to Eden Haddock Total Talent.
0:55
SPEAKER_01: I am your host, Eden Haddock.
0:58
SPEAKER_01: No guests, no sponsors, no paid promotions.
1:03
SPEAKER_01: Just one talent practitioner, still very much on the tools, talking about the things I think matter to our profession.
1:12
SPEAKER_01: And throughout November, we're doing something a little bit different.
1:17
SPEAKER_01: Thirty days, thirty episodes, one mission.
1:23
SPEAKER_01: Thirty consecutive episodes throughout November exploring the technology, services, ideas, and innovations shaping the future of talent and people while raising money for men's health.
1:40
SPEAKER_01: And if you're listening to this episode, there are three things you can do to help follow the podcast, share this episode with your network, and if you're in a position to do so, please donate to my Movember campaign.
1:57
SPEAKER_01: I'll include the link in the episode description.
2:01
SPEAKER_01: Every donation helps, every share helps, every new person we get talking about men's health helps.
2:11
SPEAKER_01: Right, episode five.
2:15
SPEAKER_01: And I've got to say the conversation behind this episode took me somewhere I wasn't expecting.
2:24
SPEAKER_01: Because I thought I was going to be talking about background checks.
2:29
SPEAKER_01: And I suppose technically I am.
2:33
SPEAKER_01: But I'm actually going to talk about something much bigger.
2:37
SPEAKER_01: Trust.
2:39
SPEAKER_01: More specifically, can we still trust a CV?
2:44
SPEAKER_01: Can we trust an application?
2:47
SPEAKER_01: Can we trust that the person applying for a role is who they say they are?
2:53
SPEAKER_01: Can we trust the qualifications they've listed?
2:58
SPEAKER_01: Can we trust the employment history?
3:02
SPEAKER_01: And perhaps the biggest question of all, has AI fundamentally changed the point at which talent teams need to start verifying candidates?
3:15
SPEAKER_01: Because I think it might have.
3:18
SPEAKER_01: And that is where this gets really interesting.
3:23
SPEAKER_01: We'll start with the trust model of recruitment.
3:29
SPEAKER_01: For most of my career, recruitment has operated on a fairly simple principle.
3:37
SPEAKER_01: Trust first, verify later.
3:42
SPEAKER_01: Someone applies for a role, they give us their CV.
3:48
SPEAKER_01: We largely assume it's accurate.
3:53
SPEAKER_01: They tell us where they've worked.
3:56
SPEAKER_01: We largely assume they worked there.
4:00
SPEAKER_01: They tell us what qualifications they have.
4:04
SPEAKER_01: Unless that qualification is legally required for the job, a lot of organizations probably don't check it.
4:14
SPEAKER_01: They tell us they have the right to work.
4:18
SPEAKER_01: Depending on the organization, we might verify that relatively early, or we might leave it until later.
4:28
SPEAKER_01: We interview them, we assess them, we hopefully conduct good behavioral interviews, maybe some technical assessment, maybe psychometric assessment, maybe work samples.
4:48
SPEAKER_01: And eventually we decide, yep, this is our person.
4:56
SPEAKER_01: Then somewhere around the offer stage, we start verifying things.
5:04
SPEAKER_01: References, criminal checks, right to work checks, qualifications were required.
5:15
SPEAKER_01: Whatever is appropriate for that organization and that role.
5:22
SPEAKER_01: And that model made sense.
5:25
SPEAKER_01: Because verification costs time.
5:30
SPEAKER_01: It costs money.
5:33
SPEAKER_01: There is administration involved.
5:37
SPEAKER_01: You don't want to background check three hundred applicants when you're only going to hire one.
5:45
SPEAKER_01: So we created this model where assessment happens first and verification happens towards the end.
5:55
SPEAKER_01: But the problem, the environment that model was built for doesn't really exist anymore.
6:05
SPEAKER_01: Because we're now entering an era where creating a convincing application is easier than it has ever been.
6:16
SPEAKER_01: And that's not automatically a bad thing.
6:20
SPEAKER_01: I've talked before on this podcast about AI helping candidates.
6:27
SPEAKER_01: I don't have an issue with someone using AI to improve the structure of their CV.
6:35
SPEAKER_01: I don't have an issue with somebody getting help articulating their experience.
6:44
SPEAKER_01: I don't think using technology automatically makes an application dishonest.
6:52
SPEAKER_01: But there is obviously a line.
6:56
SPEAKER_01: And that line gets crossed when technology stops helping someone communicate their experience and starts manufacturing experience that doesn't exist.
7:11
SPEAKER_01: AI has changed the cost of fabrication.
7:16
SPEAKER_01: Think about how difficult it used to be to create a really convincing fake CV.
7:24
SPEAKER_01: You needed to put some effort into it.
7:28
SPEAKER_01: You needed to know the terminology.
7:31
SPEAKER_01: You needed to understand the industry.
7:35
SPEAKER_01: You needed to understand the role.
7:39
SPEAKER_01: You needed to create something that sounded credible.
7:43
SPEAKER_01: But now you can take the position description, feed it into an AI tool, and ask for help tailoring an application to that role.
7:56
SPEAKER_01: And again, used ethically, that's fine.
8:03
SPEAKER_01: But we've also got automated application tools.
8:09
SPEAKER_01: We've got technology capable of generating content at a normous scale.
8:17
SPEAKER_01: We've got deep fakes.
8:20
SPEAKER_01: We've got increasingly sophisticated identity fraud.
8:27
SPEAKER_01: And Jack Gillen from Zinc made a really simple observation when I spoke with him.
8:35
SPEAKER_01: He's hearing more about fake candidates and candidate fraud.
8:42
SPEAKER_01: That's the bit I think talent needs to pay attention to.
8:48
SPEAKER_01: Because this isn't simply candidates are using Chat GPT now.
8:53
SPEAKER_01: That's yesterday's conversation.
8:57
SPEAKER_01: The bigger conversation is what happens when the cost of fabrication approaches zero.
9:06
SPEAKER_01: Creating a tailored application used to require effort.
9:13
SPEAKER_01: Creating ten required more effort.
9:17
SPEAKER_01: Creating one hundred required an enormous amount of effort.
9:23
SPEAKER_01: Technology changes that equation.
9:27
SPEAKER_01: And suddenly our recruitment processes are trying to assess a completely different volume and quality of information.
9:38
SPEAKER_01: I said something during my conversation with Zinc that I've kept thinking about since.
9:46
SPEAKER_01: We've got AI helping candidates apply for jobs.
9:52
SPEAKER_01: And then we've got AI helping talent teams assess those applications.
9:59
SPEAKER_01: So potentially AI is creating the application.
10:05
SPEAKER_01: AI is screening the application.
10:09
SPEAKER_01: AI is ranking the application.
10:13
SPEAKER_01: And eventually a human recruiter comes into the process and goes, hang on, is any of this actually real?
10:25
SPEAKER_01: That is a bizarre place for recruitment to find itself.
10:30
SPEAKER_01: And it makes verification much more important.
10:37
SPEAKER_01: So maybe we're verifying too late.
10:43
SPEAKER_01: This was probably the biggest question I walked away from the zinc conversation with.
10:51
SPEAKER_01: Do background checks still belong exclusively at the end of recruitment?
10:59
SPEAKER_01: I'm not saying they don't.
11:03
SPEAKER_01: And I'm definitely not saying we should suddenly criminal check every person who submits an application.
11:11
SPEAKER_01: That would be ridiculous.
11:14
SPEAKER_01: There are privacy considerations, candidate experience considerations, cost considerations, compliance considerations.
11:30
SPEAKER_01: And different jurisdictions will obviously have different rules.
11:37
SPEAKER_01: But perhaps some forms of verification need to move earlier.
11:42
SPEAKER_01: Identity is the obvious one.
11:46
SPEAKER_01: Right to work could be another.
11:51
SPEAKER_01: Perhaps employment verification in certain situations.
11:56
SPEAKER_01: Maybe qualification verification for certain roles.
12:02
SPEAKER_01: Siobon Sexton from Zinc said they're beginning to have conversations with organizations about this.
12:12
SPEAKER_01: She was very clear that it isn't yet some massive established trend.
12:20
SPEAKER_01: But organizations are starting to ask how they mitigate candidate fraud.
12:27
SPEAKER_01: And in some circumstances, that could mean carrying out certain checks around interview stage rather than waiting until the very end.
12:41
SPEAKER_01: And I think that conversation is going to get louder.
12:45
SPEAKER_01: Because imagine this: you've got five hundred applicants, you shortlist twenty, you interview six, three progress, you run multiple interviews, you involve hiring managers, maybe executives, maybe technical assessors.
13:11
SPEAKER_01: You invest hours and hours of organizational time.
13:17
SPEAKER_01: You select your preferred candidate, and then discover something fundamental about the application that wasn't true.
13:31
SPEAKER_01: That isn't simply a failed background check.
13:36
SPEAKER_01: That's wasted organizational capacity.
13:41
SPEAKER_01: And in a world where talent teams are being asked to become more productive, that matters.
13:52
SPEAKER_01: Maybe the future is not background checking.
13:56
SPEAKER_01: Maybe the future is progressive verification.
14:02
SPEAKER_01: Different levels of validation at different points of the process proportionate to the role and the risk.
14:12
SPEAKER_01: I think that's a really interesting conversation.
14:18
SPEAKER_01: Now, one check isn't going to solve this.
14:23
SPEAKER_01: And this is where I liked something that Siobon said.
14:29
SPEAKER_01: There isn't one magic check that says, congratulations.
14:33
SPEAKER_01: This human is definitely real, and everything they've told you is true.
14:39
SPEAKER_01: It doesn't work like that.
14:42
SPEAKER_01: She talked about a layered approach: identity, digital footprint, CV information compared against references, employment verification, qualifications, potentially information coming directly from primary sources.
15:09
SPEAKER_01: And you're looking for consistency.
15:13
SPEAKER_01: Do the pieces fit together?
15:17
SPEAKER_01: Because fraud often isn't uncovered through one enormous flashing red light.
15:25
SPEAKER_01: Sometimes it's the little inconsistencies.
15:30
SPEAKER_01: This date doesn't match that date.
15:34
SPEAKER_01: This qualification can't be verified.
15:38
SPEAKER_01: This employment history doesn't line up.
15:44
SPEAKER_01: This identity information isn't consistent.
15:49
SPEAKER_01: This reference creates another question.
15:53
SPEAKER_01: And suddenly you've got enough small signals to say, okay, we need to look more closely at this.
16:05
SPEAKER_01: That's very different from the old compliance mindset.
16:10
SPEAKER_01: Tick, tick, tick, done.
16:16
SPEAKER_01: This starts becoming candidate intelligence and risk management.
16:23
SPEAKER_01: And I suspect that's where this category of technology is heading.
16:31
SPEAKER_01: The qualification question.
16:34
SPEAKER_01: Here's an example I used in the conversation.
16:40
SPEAKER_01: I could apply for a role tomorrow and put on my CV that I've got a master's in public health.
16:48
SPEAKER_01: I don't.
16:50
SPEAKER_01: But imagine I did put it in there.
16:55
SPEAKER_01: Maybe the role doesn't technically require it.
16:59
SPEAKER_01: So nobody verifies it.
17:03
SPEAKER_01: Maybe it gives me credibility.
17:07
SPEAKER_01: Maybe it helps me look more relevant.
17:11
SPEAKER_01: Maybe it influences the hiring manager.
17:15
SPEAKER_01: And perhaps I still could have done the job perfectly with perfectly well without it.
17:21
SPEAKER_01: So does it matter?
17:25
SPEAKER_01: I think it absolutely does.
17:29
SPEAKER_01: Not because I needed the masters, but because I lied to you before I'd even joined your organization.
17:38
SPEAKER_01: That's not a capability issue anymore.
17:42
SPEAKER_01: That's a trust issue.
17:45
SPEAKER_01: Siobon made essentially the same point.
17:50
SPEAKER_01: Even when a qualification isn't specifically required to perform the role, verification can contribute to a broader understanding of whether the information a candidate has provided is truthful.
18:07
SPEAKER_01: And AI makes this harder again.
18:11
SPEAKER_01: Because fake credentials can look increasingly convincing.
18:19
SPEAKER_01: International hiring makes it harder again.
18:25
SPEAKER_01: If somebody tells me they attended a university in another country, how confident am I that I know every legitimate institution in that country?
18:36
SPEAKER_01: I don't.
18:37
SPEAKER_01: Most recruiters don't.
18:39
SPEAKER_01: That's not our expertise.
18:43
SPEAKER_01: Zinc demonstrated two approaches to qualification checking.
18:48
SPEAKER_01: Matching candidate-provided certificates or transcripts against information using AI to identify mismatches and going directly to institutions to verify information where source verification is required.
19:11
SPEAKER_01: And I think we're going to need more of that.
19:15
SPEAKER_01: Not because we should become cynical about candidates.
19:20
SPEAKER_01: I don't want recruitment to become everybody is lying until proven otherwise.
19:25
SPEAKER_01: That's horrible.
19:28
SPEAKER_01: But equally, trust doesn't mean abandoning verification.
19:34
SPEAKER_01: Good hiring needs both.
19:40
SPEAKER_01: Then, wow, the conversation got really interesting.
19:47
SPEAKER_01: Because we started talking about social media.
19:51
SPEAKER_01: And I'll admit this openly, this part fascinated me.
19:58
SPEAKER_01: Zinc offers social media and adverse media checks alongside more familiar things like criminal, credit, right to work, reference, and qualification checks.
20:16
SPEAKER_01: Now, adverse media is relatively straightforward conceptually.
20:23
SPEAKER_01: You're looking at news and other sources for potentially relevant adverse findings.
20:33
SPEAKER_01: Social media gets much more complicated.
20:38
SPEAKER_01: Because now we're entering people's public digital footprints.
20:45
SPEAKER_01: And immediately my talent brain goes, Whoa, where is the line?
20:53
SPEAKER_01: What are we checking?
20:56
SPEAKER_01: Why are we checking it?
20:58
SPEAKER_01: What is relevant?
21:01
SPEAKER_01: What isn't?
21:03
SPEAKER_01: What about political opinions?
21:06
SPEAKER_01: What about someone's sense of humor?
21:10
SPEAKER_01: What about something stupid they posted ten years ago?
21:14
SPEAKER_01: What about context?
21:17
SPEAKER_01: What about bias?
21:19
SPEAKER_01: What about protected attributes that you could discover while doing the search?
21:27
SPEAKER_01: There are some enormous questions here.
21:31
SPEAKER_01: But then I realized something slightly uncomfortable.
21:37
SPEAKER_01: Recruiters are already doing it.
21:40
SPEAKER_01: Come on.
21:41
SPEAKER_01: Come on.
21:43
SPEAKER_01: We've all Googled a candidate.
21:45
SPEAKER_01: I admitted this to Siobon.
21:48
SPEAKER_01: I've Googled candidates.
21:50
SPEAKER_01: Naturally, I've looked people up on LinkedIn.
21:54
SPEAKER_01: But I've also looked at someone's publicly available social footprint.
22:01
SPEAKER_01: And I suspect plenty of people listening to this have too.
22:06
SPEAKER_01: Sometimes you're not even looking for anything negative.
22:10
SPEAKER_01: You're curious.
22:12
SPEAKER_01: Talent people are fascinated by people.
22:17
SPEAKER_01: That's probably one of the reasons we ended up doing this job.
22:23
SPEAKER_01: But Siobon made a point that stopped me.
22:28
SPEAKER_01: What happens when you find something?
22:32
SPEAKER_01: What happens?
22:35
SPEAKER_01: You've done your unofficial Google search.
22:38
SPEAKER_01: You've stumbled across something concerning.
22:42
SPEAKER_01: Now what?
22:45
SPEAKER_01: Can you use it?
22:47
SPEAKER_01: Should you use it?
22:50
SPEAKER_01: Was the search conducted consistently across every candidate?
22:56
SPEAKER_01: Was the information relevant to the role?
23:02
SPEAKER_01: Could unconscious bias have influenced how you interpreted it?
23:08
SPEAKER_01: Would another recruiter have reached a completely different conclusion?
23:14
SPEAKER_01: Suddenly, our casual bit of Googling doesn't feel quite so harmless.
23:22
SPEAKER_01: Siobon's argument was that a standardized process can potentially create more consistency around what is being assessed and how information is surfaced.
23:37
SPEAKER_01: And I think that's worthy of debate.
23:41
SPEAKER_01: I'm not saying every company should start social media screening tomorrow.
23:46
SPEAKER_01: Far from it.
23:48
SPEAKER_01: But I am saying maybe an unofficial, inconsistent process isn't automatically more ethical than a formal one.
24:00
SPEAKER_01: That's an uncomfortable question.
24:04
SPEAKER_01: And uncomfortable questions are usually worth exploring.
24:10
SPEAKER_01: So what does zinc actually check?
24:14
SPEAKER_01: During the demo, Siobon showed me how Zinc approaches this.
24:20
SPEAKER_01: The platform looks across public social media information and identifies content against defined risk categories.
24:32
SPEAKER_01: The example report included categories around things like drugs, profanity, threats, weapons imagery, disparaging content, and other areas.
24:50
SPEAKER_01: Zinc uses AI in the process, with human analysis also involved in reviewing findings.
25:01
SPEAKER_01: But there's an important bit.
25:04
SPEAKER_01: A flag isn't a verdict.
25:08
SPEAKER_01: And I think that distinction is absolutely critical.
25:13
SPEAKER_01: Siobon gave me a brilliant example.
25:17
SPEAKER_01: A photograph containing a weapon could sound concerning until you discover that photograph is from somebody participating in clay pigeon shooting.
25:31
SPEAKER_01: Same image category, completely different context.
25:37
SPEAKER_01: That's why we need humans.
25:40
SPEAKER_01: Technology can surface information.
25:44
SPEAKER_01: Technology can identify patterns.
25:49
SPEAKER_01: Technology can flag something for attention.
25:53
SPEAKER_01: But context is everything.
25:57
SPEAKER_01: And context requires judgment.
26:02
SPEAKER_01: The system might say, look here.
26:06
SPEAKER_01: It shouldn't necessarily say, don't hire this person.
26:12
SPEAKER_01: Those are very different things.
26:16
SPEAKER_01: And that is a theme I keep coming back to on this podcast.
26:21
SPEAKER_01: The best technology isn't necessarily technology that replaces human judgment.
26:29
SPEAKER_01: Sometimes the best technology is the stuff that gives humans better information on which to exercise judgment.
26:42
SPEAKER_01: So the ethical line matters.
26:45
SPEAKER_01: I want to spend some time here because I don't want this episode to accidentally become excellent.
26:52
SPEAKER_01: Let's investigate everyone's Instagram account.
26:56
SPEAKER_01: No, that's not what I'm saying.
27:00
SPEAKER_01: If you're going to use digital footprint information in employment decisions, there need to be very clear reasons for doing it.
27:12
SPEAKER_01: There needs to be policies.
27:15
SPEAKER_01: There needs to be consistency.
27:19
SPEAKER_01: There needs to be an understanding of local legislation.
27:25
SPEAKER_01: There needs to be proportionality.
27:29
SPEAKER_01: And there absolutely needs to be human judgment.
27:35
SPEAKER_01: Siobon made the point that the acceptable threshold will vary by organization, role, jurisdiction, and policy.
27:47
SPEAKER_01: And that social media checking needs to sit alongside a clear organizational social media policy.
27:56
SPEAKER_01: That makes sense.
27:59
SPEAKER_01: Because the risk profile of somebody working with vulnerable children is different from somebody working in another environment.
28:10
SPEAKER_01: Someone acting publicly as a representative of a major consumer brand may carry different considerations.
28:21
SPEAKER_01: Someone working in a heavily regulated industry may be subject to requirements that simply don't apply elsewhere.
28:31
SPEAKER_01: This cannot be one size fits all.
28:35
SPEAKER_01: And personally, I would be incredibly uncomfortable with an employer using this kind of technology to police perfectly lawful differences of opinion.
28:49
SPEAKER_01: That's not what good talent practice looks like.
28:53
SPEAKER_01: But equally, if somebody has a public digital footprint containing serious discriminatory content, threats, or extremist material, I think organizations are entitled to ask whether that presents a legitimate workplace risk.
29:16
SPEAKER_01: And that's where this conversation gets difficult.
29:19
SPEAKER_01: Because privacy matters, freedom of expression matters, fair hiring matters, and organizational duty of care matters too.
29:34
SPEAKER_01: All of those things can be true at the same time.
29:40
SPEAKER_01: Your digital footprint, though, it doesn't end when you get hired.
29:46
SPEAKER_01: Another question came up.
29:50
SPEAKER_01: Why do we assume verification stops once somebody becomes an employee?
29:59
SPEAKER_01: Think about a criminal record check.
30:02
SPEAKER_01: You complete it before somebody joins.
30:06
SPEAKER_01: It's clean, great.
30:10
SPEAKER_01: But that only tells you something about a moment in time.
30:15
SPEAKER_01: It doesn't guarantee nothing changes afterwards.
30:20
SPEAKER_01: Same with sanctions, adverse media, directorships, potential conflicts, public social media activity.
30:35
SPEAKER_01: Siobon said they're seeing growing interest in rechecking certain categories later in the employee lifecycle.
30:45
SPEAKER_01: Not historical information that doesn't change.
30:50
SPEAKER_01: There's not much point continually checking whether someone worked somewhere ten years ago.
30:57
SPEAKER_01: But information that can change over time, well, that's different.
31:03
SPEAKER_01: And again, this requires care.
31:07
SPEAKER_01: Because continuous monitoring of employees can get dystopian very quickly if it's poorly designed.
31:15
SPEAKER_01: I don't want to work in a world where an employer is digitally staring over my shoulder every second of the day, right?
31:25
SPEAKER_01: But there are roles and environments where ongoing verification may be proportionate and legitimate.
31:37
SPEAKER_01: The challenge for people teams is going to be finding that line and explaining it transparently.
31:48
SPEAKER_01: Because if employees don't understand what is being checked, why it's being checked, and how information will be used, you've got a trust problem of your own.
32:04
SPEAKER_01: So where does zinc fit into this?
32:07
SPEAKER_01: Let me talk specifically about Zinc now.
32:11
SPEAKER_01: Because this entire episode came from spending time with Siobon Sexton and Jack Gillen and getting a proper walkthrough of what they've built.
32:23
SPEAKER_01: Zinc is a SaaS background checking platform, headquartered in London and operating globally.
32:33
SPEAKER_01: And what I liked about the positioning is they're not pretending they've invented background checking.
32:40
SPEAKER_01: Background checking has existed forever.
32:44
SPEAKER_01: Their argument is that too much of it still operates using old manual processes: chasing candidates, chasing referees, manually uploading documents, moving information between systems, waiting, following up, waiting again.
33:07
SPEAKER_01: Their proposition is essentially where can automation remove unnecessary friction without removing appropriate human control.
33:20
SPEAKER_01: That's really interesting to me.
33:24
SPEAKER_01: Because background checking isn't where I want my talent team spending its strategic energy.
33:32
SPEAKER_01: I want talent people talking to candidates, talking to leaders, understanding workforce risk, building succession, thinking about capability, thinking about REM, thinking about workforce planning, thinking about where the organization is heading.
33:53
SPEAKER_01: I don't want brilliant talent practitioners spending half a day chasing a document that technology could have retrieved or processed more effectively.
34:05
SPEAKER_01: That makes sense.
34:07
SPEAKER_01: Automation should remove administration, not accountability.
34:16
SPEAKER_01: The real outcome isn't faster checks.
34:19
SPEAKER_01: Here's where I think the real value sits.
34:22
SPEAKER_01: Yes, speed matters.
34:24
SPEAKER_01: Yes, candidate experience matters.
34:27
SPEAKER_01: Yes, automation matters, right?
34:30
SPEAKER_01: We know that.
34:32
SPEAKER_01: But the real outcome isn't we completed a background check faster.
34:38
SPEAKER_01: The outcome is we reduced organizational risk without creating unnecessary friction.
34:46
SPEAKER_01: And ideally, we gave talent time back.
34:50
SPEAKER_01: Siobon talked about customers seeing significant reductions in the manual administration associated with checking, allowing teams to spend more time on strategic work.
35:04
SPEAKER_01: That's the metric I care about, not look how clever the software is.
35:10
SPEAKER_01: Right?
35:11
SPEAKER_01: It's where can my people do the work that they couldn't do before?
35:19
SPEAKER_01: If technology gives my talent team hours back, I don't want to reward them by giving them another 50 requisitions.
35:29
SPEAKER_01: I want them to use that capacity to become better talent professionals, better advisors, better workforce planners, better storytellers, better partners to the business, better humans with candidates.
35:46
SPEAKER_01: That's the promise of automation that actually excites me.
35:50
SPEAKER_01: Not fewer humans, but more human capacity.
35:55
SPEAKER_01: So can you still trust a CV?
35:59
SPEAKER_01: Yes, I think you can.
36:03
SPEAKER_01: I don't want this episode to leave everybody paranoid.
36:08
SPEAKER_01: Most candidates are not fraudsters.
36:12
SPEAKER_01: Most people are not fabricating their entire career.
36:16
SPEAKER_01: Most people are trying to find a job and present themselves in the best possible way.
36:23
SPEAKER_01: Let's not build recruitment around suspicion, but let's also acknowledge reality.
36:30
SPEAKER_01: The tools available to people have changed.
36:34
SPEAKER_01: The scale has changed.
36:36
SPEAKER_01: The sophistication has changed.
36:39
SPEAKER_01: The ability to fabricate convincing information has changed.
36:45
SPEAKER_01: Therefore, our processes have to change too.
36:51
SPEAKER_01: So, final thought.
36:54
SPEAKER_01: The thing I liked most about my conversation with zinc wasn't actually the technology.
37:00
SPEAKER_01: It was the question the technology forced me to ask.
37:04
SPEAKER_01: What does trust mean in recruitment when information is increasingly easy to manufacture?
37:10
SPEAKER_01: That's bigger than zinc?
37:12
SPEAKER_01: That's bigger than background checks?
37:15
SPEAKER_01: That's a workforce 5.0 question.
37:18
SPEAKER_01: Because we're building a world where humans and technology increasingly work together.
37:25
SPEAKER_01: So the answer has to be better systems, better verification, and better human judgment.
37:34
SPEAKER_01: Technology can surface the signal.
37:37
SPEAKER_01: Humans still need to understand what it means.
37:41
SPEAKER_01: And I think we're going to be having a lot more conversations about that over the next couple of years.
37:48
SPEAKER_01: A huge thank you to Siobon and Jack from Zinc for giving me their time, showing me the platform, most importantly, being willing to have a genuinely open conversation about where this space is heading.
38:03
SPEAKER_01: As always, they haven't paid to be here.
38:06
SPEAKER_01: This isn't sponsored.
38:08
SPEAKER_01: They haven't appeared as guests.
38:11
SPEAKER_01: What you've heard are my thoughts and my perspective after spending time understanding what they've built.
38:18
SPEAKER_01: If you're interested in Zinc, I'll include links to Zinc, Siobon, and Jack in the episode description.
38:25
SPEAKER_01: And that brings us back to why we're doing all of this.
38:28
SPEAKER_01: Movember.
38:30
SPEAKER_01: 30 days, 30 episodes, one mission.
38:35
SPEAKER_01: This month isn't really about producing 30 podcast episodes.
38:39
SPEAKER_01: That's just the vehicle.
38:41
SPEAKER_01: The mission is men's health.
38:44
SPEAKER_01: Movember funds work across mental health and suicide prevention, prostate cancer and testicular cancer.
38:52
SPEAKER_01: So I'm asking every person listening to do something.
38:56
SPEAKER_01: If you've enjoyed this episode, share it.
38:59
SPEAKER_01: If you know someone in talent who would get something from this conversation, send it to them.
39:05
SPEAKER_01: If you're enjoying this 30-day experiment, follow Eden Hadictotal Talent on Apple Podcasts or Spotify.
39:12
SPEAKER_01: And if you're able to, please donate.
39:16
SPEAKER_01: The link to my Movember fundraising page is in the episode description.
39:23
SPEAKER_01: I'll be back tomorrow with episode six.
39:26
SPEAKER_01: Until then, keep challenging the way we think about talent.
39:31
SPEAKER_01: Keep the humans at the center of the technology.
39:35
SPEAKER_01: And let's keep doing some good along the way.
39:38
SPEAKER_01: I'm Eden Haddock.
39:40
SPEAKER_01: This is Total Talent.
39:42
SPEAKER_01: I'll see you tomorrow.