00:00 (upbeat music)
00:02 - Hi everybody, I'm Diane Brady.
00:04 I'm here with Deco, who is the CEO of Recruit Holdings,
00:07 Glassdoor, and indeed we're in AI house,
00:10 which of course, I think nothing embodies the chaos
00:13 and the enthusiasm for AI,
00:15 like standing where we're standing.
00:17 What do you think about this?
00:19 It's been the big theme at Davos this year.
00:21 - Yeah, of course, like that last 18 month or 12 month,
00:25 like the AI thing is becoming to be more and more real.
00:29 And of course I'm excited as a one technologist,
00:33 but,
00:34 (laughing)
00:35 but, you know, when we actually think about,
00:38 even 20 years ago, people are so excited about internet,
00:42 but, you know, I still think it takes time
00:45 because we need to keep training AI model
00:48 to be more like a realistic, you know,
00:52 that support for the real society
00:54 or real execution of the society.
00:58 So it's, it will, you know,
01:01 like change a lot of like our, our, our, you know, life.
01:06 - Yeah.
01:07 - But it just takes time.
01:08 - I suspect, are you talking about
01:11 what it's going to do to jobs?
01:13 Because when you think about,
01:14 there's some excitement maybe that's,
01:16 when it comes to displacing humans and jobs,
01:19 that's where the fear factor comes in.
01:22 So you, do you think we're just sort of overestimating
01:25 the fear factor right now?
01:27 Is that what it is that you think we're,
01:28 is too much hype?
01:30 - Yeah, you know, our research is showing AI
01:34 will affect almost all job seekers or all workers,
01:39 of course, but the important thing is,
01:43 it's going to be very difficult
01:44 to fully replace human being jobs.
01:49 And one example I like is, okay,
01:52 advanced AI, somebody built fully automated airline.
01:57 You know?
02:00 - I will not fly a fully automated airline.
02:02 Can I point that out?
02:03 - Can we just have one pilot at least, just in case?
02:07 I think that's the situation we're seeing.
02:10 What I'm seeing is like, of course we have a lot of data.
02:14 We are trying to build a lot of AI function
02:19 to sometimes automate procedures of hiring
02:23 or like to support human being recruiters.
02:27 But we, what we are actually thinking is,
02:30 probably we're going to need the human being aspect
02:35 to finally check or to decide the hiring.
02:39 - A lot of data to put into it,
02:41 jobs that'll change.
02:42 I mean, I want to talk about what's happening
02:43 on the ground because it seems like
02:46 when you look at the job market,
02:48 things are pretty good.
02:50 And yet the feelings about the job market aren't as good.
02:53 Do you see that disconnect between the companies
02:56 that you oversee?
02:58 - I've been saying the same thing over a year and a year.
03:02 What we are, what people are missing
03:05 is the shortage of labor supply.
03:08 For example, like 10 years ago, 15 years ago,
03:12 in the US, we had 2 million, 3 million additional
03:17 like working age population every year.
03:21 Meaning if we didn't have additional 2 million jobs,
03:25 we're going to have 1.5, 2% higher unemployment rate.
03:30 Meaning 2018, 2019, we had almost zero
03:36 additional working age population in the US.
03:38 - So the demographics have not shifted.
03:40 - It's been getting like, having like aging workforce.
03:45 So as a result, of course, we might be able
03:50 to have soft landing situation,
03:52 but the big factor of that is actually
03:55 the short supply of labor force.
03:59 So of course, the hiring demand will be going down.
04:04 It's cooling down from the high peak,
04:09 from the COVID recovery,
04:11 but still we are expecting a little bit longer term
04:16 tighter labor market.
04:19 - Well, let me ask about,
04:20 'cause if we unpack that a little,
04:21 when we talk about labor shortages,
04:23 the data engineers are not the ones who are worried.
04:26 It's the people who are at the lower end
04:29 of the income spectrum,
04:30 people who've already felt a bit displaced
04:32 or their wages haven't grown as much.
04:35 When you look at the spread of whether it's optimism
04:39 or job growth, is there not some valid fear
04:43 among that tier of people who are not growing
04:47 as a percentage of the workforce?
04:49 - I think one thing I wanted to mention is,
04:53 long-term trend was like white collar salary.
04:59 The gap between white collar salary
05:01 and blue collar salary was coming to be wider.
05:05 But the last year we saw that it's got
05:08 almost like opposite trend.
05:10 - Because of AI? No.
05:12 - We'll see.
05:13 But as I said, the basic trend is we don't have
05:17 enough supply of labor force.
05:18 Maybe the improvement of productivity for white collar
05:23 with AI, some technologies,
05:27 but I think in general, all developed countries
05:31 will have some kind of labor shortage.
05:34 So as a result, we might not have high unemployment rate
05:39 like we had like 10 years ago, 15 years ago,
05:44 but we might have relatively high employment rate
05:49 because if you want to hire workers for construction job
05:54 or in a primary job or nurses,
05:58 it's gonna be difficult to hire.
06:00 - When you talk, I start to think about what happened
06:03 in Japan, which has been an early mover
06:06 with regard to the trends you're talking about.
06:08 You also don't have a lot of growth in those situations
06:11 when there's a mismatch, especially when you need
06:14 skilled labor to kind of accelerate innovation.
06:17 So let me get back to that principle of,
06:20 on the emotional level, are we right to be worried?
06:23 - I think, again, like Japan is extremely,
06:27 extremely example of the aging workforce.
06:30 They're having 1%, 2% less working age population
06:34 every year.
06:36 So now, actually, for example, like one big restaurant chain
06:41 which have like 2000 restaurants,
06:46 they decided to have 3000 food delivery in Japan.
06:51 But as a result, they have better retention of workers.
06:57 They started to hire more like aged workers
07:01 because they don't need to work that way.
07:04 So I'm thinking, of course, it's challenging,
07:08 but still, when we think about the future
07:10 and AI and technology, it might be a good test field
07:15 to test new technologies,
07:17 how technology can work with human beings.
07:21 - What do you see in the near term?
07:22 So we're 2020, we're still election year.
07:25 Jobs and the economy are always critical to who wins.
07:29 What are you seeing in terms of the trend lines,
07:33 like say the next six to 12 months?
07:36 - Yeah, so I'm still thinking we're gonna have
07:40 a little bit mild recession.
07:42 I would not say that-- - So not a soft landing.
07:45 I don't know what a soft landing means, by the way.
07:47 What does that even mean?
07:48 - But I've been checking the labor market.
07:53 When I'm thinking about the unemployment rate,
07:57 it's not gonna be going up 5%, 6%.
08:00 Even 5%, it's a historical norm.
08:02 - But people feel worse than the numbers suggest.
08:05 - Because of the gap between wage inflation
08:09 and actual inflation.
08:11 But now, as I said, we might see
08:15 like a stubborn wage inflation.
08:20 So I would say for the next 12, 18 months,
08:24 even the economy is getting worse,
08:26 it's not gonna be like a terrible situation
08:30 because if, let's say, 4%, 5% people can keep their job,
08:35 the consumer numbers should not be that bad.
08:40 So it's not gonna be 2009, 2010 type of situation
08:45 because of the big demographic change
08:48 in many developed countries, especially--
08:52 - Are there any other trends that you're seeing
08:54 from the data?
08:55 Again, I wanna be respectful, you've got both Glassdoor
08:58 and you're also seeing on the recruiting side.
09:01 What else are you seeing that even early trends
09:05 that you would put on our radar?
09:07 - I would say the full example.
09:11 Numbers we are seeing is, when we compare
09:17 end of 2019 or beginning of 2020, before COVID,
09:21 we added, in the US, we added 2.8 million,
09:25 2.9 million workers.
09:27 But 90% of them are non-native Americans,
09:32 Polish-born workers.
09:36 So I still think, when we think about the actual matching,
09:41 we are having less skilled laborers
09:45 who have been doing car technicians
09:48 or constructions or nurses.
09:51 And we're getting more immigrants,
09:53 but we need to keep training the workforce.
09:57 Otherwise, for example, number of job posting
10:01 to hire nurses is still 40%, 50% higher than 2019.
10:06 - Than the number of nurses, yeah, that's the time of year.
10:08 - Yes, it's just a pure labor shortage.
10:13 - Are there particular areas of the country
10:14 where you see a particular gap or growing gap
10:18 that we should be worried about?
10:20 - I would say healthcare for all countries.
10:25 And still, when I talk with some government people,
10:31 sometimes they still think,
10:33 okay, we need more healthcare jobs.
10:34 I'm telling them, no.
10:37 Probably the younger generation
10:39 don't wanna do that kind of hard jobs.
10:41 So we need to change their mindset.
10:45 This is an extremely important job for society.
10:48 And probably we also need to think
10:52 how we can pay more for healthcare workers
10:55 or even teachers.
10:57 Are we really good to have this supply?
11:02 - Are you seeing wages go up in those areas?
11:05 You said it's a communication challenge.
11:07 - Yes.
11:08 - So employers recognize it's more that
11:10 people they're trying to reach
11:11 aren't necessarily appreciating.
11:13 Anything else, especially from Davos or otherwise?
11:15 I know that I'm stereotyping you
11:18 as a person to talk about jobs as you should.
11:21 Are there other things that you're thinking about here
11:24 and in general as a leader?
11:26 - Yeah, as I said, in general,
11:29 reskilling is a very important topic
11:31 for Davos for many, many years.
11:33 But I just wanna add,
11:36 how can we have a good training
11:39 for the skilled essential workers?
11:43 Not only tech workers, right?
11:46 So especially when we think about the future
11:49 of AI technology,
11:52 we will definitely need actual workers
11:56 for construction, farmer, car technicians, nurses.
12:00 But sometimes in Davos,
12:02 people are so focusing more on
12:05 white-collar, high-paid workers.
12:07 But when we think about the actual society,
12:12 through our data,
12:14 still 70% people are working for blue-card duties.
12:19 So I think when we think about the actual society
12:24 to be better,
12:26 how can we think about,
12:30 how can we be more to these actual essential workers
12:34 has been the challenge for the whole society.
12:37 That's how we are thinking.
12:38 - Excellent, it's a good message to bring.
12:40 Thank you for joining us.
12:41 - Thank you so much.
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