WEBVTT

1
00:00:00.200 --> 00:00:04.480
- Jessica, LinkedIn is a forum
for conversation and ideas.

2
00:00:04.480 --> 00:00:05.920
We're here at Davos,

3
00:00:05.920 --> 00:00:07.240
when you look at the conversation

4
00:00:07.240 --> 00:00:08.960
that's been happening on LinkedIn,

5
00:00:08.960 --> 00:00:10.120
what's been the most interesting?

6
00:00:10.120 --> 00:00:11.560
What's surprised you?

7
00:00:11.560 --> 00:00:15.400
- Great. Yes, well, so many things
are exciting and bubbling up,

8
00:00:15.400 --> 00:00:17.600
both on the ground and on the platform.

9
00:00:17.600 --> 00:00:21.000
I think there's a real
misconception in a lot of circles

10
00:00:21.000 --> 00:00:24.400
that AI is killing entry level jobs.

11
00:00:24.400 --> 00:00:28.400
And, we just published our
LinkedIn labor market report.

12
00:00:28.400 --> 00:00:30.760
And, we do not see that in our data.

13
00:00:30.760 --> 00:00:33.400
So, we have 1.3 billion
people on the platform,

14
00:00:33.400 --> 00:00:35.520
70 million companies;

15
00:00:35.520 --> 00:00:38.320
and our data shows that entry level jobs

16
00:00:38.320 --> 00:00:41.000
are not doing anything differently

17
00:00:41.000 --> 00:00:44.000
than the overall macro-economy and hiring,

18
00:00:44.000 --> 00:00:45.520
which is sluggish.

19
00:00:45.520 --> 00:00:46.600
Now, you add on top of that,

20
00:00:46.600 --> 00:00:49.720
there are a number of new
jobs being created by AI,

21
00:00:49.720 --> 00:00:52.120
and we're calling them new collar jobs.

22
00:00:52.120 --> 00:00:55.920
600,000 AI data center
jobs have been created.

23
00:00:55.920 --> 00:00:59.480
Many, many other jobs in the
AI sphere are blossoming.

24
00:00:59.480 --> 00:01:02.560
So, I think we need to have a
really data-based conversation

25
00:01:02.560 --> 00:01:04.880
about what's actually happening in labor.

26
00:01:04.880 --> 00:01:07.200
- So, AI does something else,

27
00:01:07.200 --> 00:01:09.920
it enables people to create
all sorts of content,

28
00:01:09.920 --> 00:01:12.560
and sometimes they're not
even creating the content

29
00:01:12.560 --> 00:01:14.720
but have the AI do it almost on its own.

30
00:01:15.360 --> 00:01:18.520
What does that mean for
a platform like yours

31
00:01:18.520 --> 00:01:21.280
that is uniquely trusted
in the marketplace?

32
00:01:21.280 --> 00:01:22.400
How do you retain that?

33
00:01:22.400 --> 00:01:25.640
- Yeah so, "AI slop," or "fake stuff,"

34
00:01:25.640 --> 00:01:29.200
is becoming a really big
issue in a lot of places.

35
00:01:29.200 --> 00:01:30.000
We're very fortunate,

36
00:01:30.000 --> 00:01:32.320
because people on LinkedIn are themselves;

37
00:01:32.320 --> 00:01:35.520
they're real people, as
opposed to some other places.

38
00:01:35.520 --> 00:01:36.480
So, that helps.

39
00:01:36.480 --> 00:01:38.240
So what we're doing is

40
00:01:38.280 --> 00:01:42.640
we are marking AI-generated
images in the feed

41
00:01:42.640 --> 00:01:43.520
with a watermark

42
00:01:43.520 --> 00:01:46.440
so that people will know
it's generated with AI.

43
00:01:46.440 --> 00:01:48.640
That doesn't mean it's bad or good,

44
00:01:48.640 --> 00:01:51.000
but we believe people
have a right to know.

45
00:01:51.000 --> 00:01:52.720
Then, with written content,

46
00:01:52.720 --> 00:01:54.960
we are scanning content in the feed

47
00:01:54.960 --> 00:01:57.960
to try to determine what is mass-produced,

48
00:01:57.960 --> 00:01:59.840
or GenAI produced,

49
00:01:59.840 --> 00:02:03.360
and we are giving more
preference in the feed

50
00:02:03.360 --> 00:02:06.280
for content written by real people,

51
00:02:06.800 --> 00:02:09.720
and we believe that that
elevates the quality of the feed.

52
00:02:09.720 --> 00:02:13.800
And, again, the network
is based on real people sharing ideas.

53
00:02:13.800 --> 00:02:17.040
- AI is not just impacting
content, as we know,

54
00:02:17.040 --> 00:02:18.560
it's impacting talent.

55
00:02:18.560 --> 00:02:20.080
What advice would you have,

56
00:02:20.080 --> 00:02:23.640
both for the candidate
and for the employer

57
00:02:23.640 --> 00:02:26.440
in this moment in time about
how to address the questions

58
00:02:26.440 --> 00:02:28.200
and the opportunities for AI?

59
00:02:28.480 --> 00:02:32.000
- Yes so, we see a lot
of employment activity,

60
00:02:32.000 --> 00:02:34.200
and I would say, obviously,

61
00:02:34.200 --> 00:02:37.080
everyone needs to be getting AI skills:

62
00:02:37.080 --> 00:02:41.240
learning tools, experimenting,
building your AI fluency,

63
00:02:41.240 --> 00:02:44.200
and being able to demonstrate those skills

64
00:02:44.200 --> 00:02:45.440
and talk about those skills

65
00:02:45.440 --> 00:02:47.920
in your LinkedIn profile and experience.

66
00:02:47.920 --> 00:02:50.800
That will become table
stakes for everyone.

67
00:02:51.120 --> 00:02:55.960
Also, good old-fashioned
skills like human judgment,

68
00:02:55.960 --> 00:02:58.920
critical thinking, good writing,

69
00:02:58.920 --> 00:03:01.000
those skills will remain,

70
00:03:01.000 --> 00:03:03.880
and actually increase in importance.

71
00:03:04.520 --> 00:03:08.320
Because everyone will be
saving enormous time and effort

72
00:03:08.320 --> 00:03:10.600
through using AI, which is great,

73
00:03:10.600 --> 00:03:13.520
but then human judgment
becomes even more important,

74
00:03:13.520 --> 00:03:15.680
and the ability to communicate clearly.

75
00:03:15.680 --> 00:03:18.240
We also advise all of
our employer partners

76
00:03:18.240 --> 00:03:20.680
to focus on skills-based hiring,

77
00:03:21.320 --> 00:03:23.840
because we don't believe
that pedigree, you know,

78
00:03:23.840 --> 00:03:26.520
"Did you go to X University?"

79
00:03:27.000 --> 00:03:30.240
"Are you from X slice of society?"

80
00:03:30.240 --> 00:03:32.960
We believe in skills-based hiring,

81
00:03:32.960 --> 00:03:35.800
and so people adding skills
to their LinkedIn profile,

82
00:03:35.800 --> 00:03:39.640
developing skills, and employers
focusing on those skills

83
00:03:39.640 --> 00:03:42.560
yields a six times higher candidate pool.

84
00:03:43.000 --> 00:03:44.040
- Amazing.

85
00:03:44.040 --> 00:03:45.200
Jessica, thank you so much.

86
00:03:45.200 --> 00:03:46.640
- Thank you, Russell. It's a pleasure.

87
00:03:46.640 --> 00:03:49.200
(bright music)