Latest / The In-Between Tech and Trust Podcast / Parenting, Tech & Transformation in Times of Synthesized Knowledge (EP 18)

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Parenting, Tech & Transformation in Times of Synthesized Knowledge (EP 18) · The In-Between Tech and Trust Podcast

0:14
Hello, this is Eva and you're listening to the In Between Tech
0:18
and Trust podcast. And this week's episode is quite
0:21
special because I talked to Chief Transformation Officer
0:25
Grisha Pavlotsky from Miro. And Miro is the collaboration
0:29
board that probably everyone of you has already used.
0:32
And the interesting part is that when Grisha and I met, we dove
0:36
into a rabbit hole and it's not what you think.
0:39
It's not transformation, collaboration teams and how you
0:42
pick the right skills for incorporating AI in
0:45
collaboration, even though that was part of our conversation as
0:50
well. We talked about how to raise
0:52
children in the age of synthesized knowledge and what
0:57
it means to provide them with background information, skills,
1:01
mindset, and also raising them in a way that they are prepared
1:05
for what's to come. So this week's episode covers
1:08
quite a lot of perspective use, but also dives deep into the way
1:15
that technology shapes trust not only in a professional but also
1:19
in the private areas of our lives.
1:25
Hi, Grisha, and welcome to the In Between Tech and Trust
1:28
podcast. Hi Eva, thank you so much.
1:30
This is my first podcast in my life in that girl.
1:33
I want to start our conversation about technology systems, but
1:38
also from a personal view of what trust means to you on like
1:42
a personal level, but then again, also at the intersection
1:46
of technology and transformation.
1:48
My background is I spent half of my life in various leadership
1:52
roles. So the, the concept of trust was
1:56
always important for me because I've built teams, I LED teams, I
1:59
was a member of the team myself, LED large organizations.
2:02
Building trust, building empowered teams, high performing
2:04
teams was a big, big part of my life.
2:06
So my current formula for trust, if you will, this is again, this
2:09
is not a final truth, but my current formula is consist of
2:12
two things. Trust consists of intent and
2:15
understanding the decision making framework, right?
2:17
So I'll, I'll unpack that intent means for me to say that I have
2:22
trust in you and I am working with you and I'm we can build
2:24
the parallel between human trust between humans and trust between
2:27
technology. But I do believe it's, it's
2:29
valuable to talk about human trust and how that translates
2:32
into technology world. For me to have a, a degree of
2:34
trust, I need to understand that we're standing on the same place
2:37
as far as our intent and what are we solving for?
2:41
Do we are we both aligned on what our final goal and what
2:44
good looks like? Right.
2:45
We can have a really good alignment about what the final
2:48
goal is, but very different definitions of what good looks
2:50
like. So that's the intent part.
2:52
Are we aligned on the intent? And the second part is around,
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am I clear how your brain works? Like what, what's under the
2:59
hood? What's the mental model, your
3:00
decision making frameworks? How do you challenge yourself?
3:03
What's, what methods do you use to get to, to get to the
3:06
outcome? So understanding what's under
3:08
the hood is the second part. So that's like intent plus
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decision making framework. Those two components will decide
3:15
whether I personally have a trust with someone.
3:17
And the interesting direction that you directly took is that
3:21
it's bidirectional and some sort.
3:23
But now you and myself, we're collaborating in teams and also
3:27
we've collaborated in global systems.
3:29
So your formula gets even more complex the more people are
3:34
integrated into those, right? Or how would you say it?
3:37
I think you're spot on actually, because we were talking about
3:41
binary between two humans, right?
3:42
And then when you build a team of 5-7 people, I don't know what
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the arithmetical formula is, but there is a exponential number of
3:49
combinations of, of how you build the choice between teams.
3:52
And then even in the technology world now, because each one of
3:56
us have access to AI tools, we're proficient.
3:58
We go in, we come to team discussions feeling much more
4:01
prepared. And a lot of times we even go
4:04
outside of our domain area. So we have a point of view or
4:06
opinion on things that we're not experts in.
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But because we've researched and with the deep thinking and
4:12
whatever we wipe coded, we we bring a much more informed and
4:16
broader point of view to the meeting.
4:17
So it's now the complexity is not just arithmetical.
4:20
It's not only like multiplied by five people, but it's also five
4:23
people that are to various degree equipped by high level of
4:27
confidence. And I say that carefully, like
4:30
high level of confidence, that they also bring a high degree of
4:33
expertise to the rooms. So that if you unpack that, then
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my formula needs to be applied not only to the human to human
4:40
iteration, but also if you ever bring some artifact to a team
4:43
meeting, I need to know which models did you use?
4:46
What prompt did you use? What context did you use?
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Do I trust you to work with your AI in the same in a consistently
4:53
same high quality way as I am so that we can connect the
4:56
artifacts and then continue the discussion at the human level?
4:59
100% you're a spot on. And I mean from the current
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technological conversations, all of us are supposed to have and
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maybe even already have coded their own AI agents and like we
5:11
build up AI genetic systems that we collaborate with and so on.
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So that is also something that then requires joint design.
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So I think the over empathy that we need to look into how we
5:25
design such AI and humans systems in order for us to trust
5:29
each other when we get into like those conversations gets even
5:32
more important. How would you say we can ensure
5:36
that that there is like the sort of transparency or at least a
5:39
common understanding that what we bring into the conversation
5:43
creates this underlying layer of trust?
5:46
So if we're talking about designing, let let me play this
5:49
back to you and let's see if I'm, I'm hitting your question
5:51
right. And they told me if, if I don't.
5:53
But when you say the designing the system, it goes back to,
5:56
again, shared understanding of what we as a team collectively
5:59
are solving for, but also the understanding of guardrails,
6:03
right? Because we all need to
6:04
understand what's below the line, what's under the line such
6:08
that when the agentic system starts working, it executes
6:10
within the boundaries of what we as a team deem acceptable.
6:14
Otherwise, I mean, the teamwork will still happen, but it will
6:17
just significantly slow us down down the road.
6:19
So I think when I, when I say as a team, when we need to align on
6:23
what we're solving for, we should also align on what's off
6:26
limits, what's the guardrails, because we're going to be
6:29
dealing with a non deterministic systems and, and the outcomes
6:32
are probabilistic. They will be within the sphere
6:35
of acceptable, but we will have some outliers and, and we as a
6:38
team, we need to understand upfront how we're going to deal
6:40
with those. Well, first of all, how to how
6:42
to identify those outliers that how do how do we know that this
6:45
particular probabilistic outcome falls outside of the spectrum of
6:48
what we agreed acceptable, how to identify it and how to deal
6:51
with it so. What are you currently solving
6:54
for on a professional but also on a personal level?
6:59
I'm so on the personal level, I'm raising for kids, trying to
7:02
figure out what to prepare them for in the future.
7:05
I have a older girl, she's a freshman in college.
7:08
We just took her to to university and then two
7:11
teenagers and one small ones also have 4 kids.
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Questions come up what to study, what to prepare themselves.
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So I'm I'm constantly evolving and like think evolving in my
7:19
thinking about what's going to be important in the future.
7:22
That's occupies big part of my life at the personal level.
7:25
Interestingly enough, same questions we're asking
7:28
internally as a company. As we're going through another
7:31
wave of transformation internally, a big question on
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the table is what does the skill set of the future look like?
7:36
What kind of people should we hire?
7:38
What good looks like when it comes to performance?
7:40
Do the teams look the same as a composition of teams and
7:44
responsibilities? So apart from bringing a cool
7:48
technology to the market, we're also rethinking what the new
7:51
ways of working look like. And, and, and a strong talent.
7:54
We just hosted a large gathering of 50 CX OS at our office
7:58
yesterday and I facilitated 4 round tables and that was what
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the new talent model looks like. For the futures consistent
8:06
theme, it's top three together with security adoption and the
8:10
talent model like those 3 themes come through consistently as top
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of mind for CX OS. Let's linger with the aspect of
8:17
you being a parent of Ford also in quite like interesting times
8:22
of development from their personality level.
8:24
And I could see that you also like working at the intersection
8:28
of like transformation Tekken teams.
8:30
You have an opinion about it also like quite, you know, basis
8:34
on how you enter the conversation with your children.
8:37
Can you let us know a bit of how you approach it and also what
8:41
the current ways of interactions are that you choose to provide
8:46
them with? So I like mental models.
8:48
It's just, it's, it's easier. I'm a big fan of different
8:51
frameworks. It's just structures you're
8:53
thinking and at least tells you how you got to the, to the
8:56
opinion that you have. So when I think about like what
8:58
to prepare my kids for, I'm asking myself, I'm not, I'm by
9:01
far not the first parent on this planet and probably not the not,
9:04
not the last. So a lot of generations of
9:06
parents ask this question. So what is different about me
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asking this question today? So that's the first thing, like
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what makes it different today from what it was 10 years ago,
9:13
50 years ago, etcetera. And it's obvious that what makes
9:16
it different that our kids will have infinite access to
9:20
knowledge, but not only the knowledge, but also they will
9:24
have infinite access to synthesis and synthesis I'm
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using with a, with a small word of S because the way the AI
9:32
models are coming up with, with the answer, a lot of times if
9:35
you're not careful about the question you ask, it comes out
9:37
with a definitive answer, the absolute claim for truth.
9:40
And an educated or unprepared user can take that as a not just
9:44
a data point, but actually as a synthesized conviction of
9:47
synthesized point of view, which makes it super dangerous because
9:51
then an unprepared user can say if somebody already synthesized
9:55
the data and information for me. So now what I'm getting is
9:58
basically a ready food. I can consume it, I can eat it.
10:01
I don't have to work for it, right?
10:03
Like, So what we've been taught to synthesize, convert facts
10:06
into point of view. If our kids are going to get be
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getting, you know, this processed food, it's like the
10:12
synthesized point of view, will it encourage them to stop
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thinking and generating these ideas themselves?
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So one one thing that I'm preparing my kids for is I'm
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saying, I know this going to happen like this.
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I know that the puck is skating that way.
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I want to teach my kids to recognize when what they've been
10:29
fed is actually not the fact that it was actually pre
10:33
synthesized point of view. And I'm teaching them to
10:35
challenge things and ask provocative questions.
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And people call it critical thinking, but but the concept of
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saying what I'm looking at, is it the fact or is it point of
10:45
view? And if it's a point of view,
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whose point of view is it? And that's a big question when
10:48
it comes to AI models, we really don't know.
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We have no visibility on data set that they were trained.
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And I think that's going to change in the future.
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I think in the future the model providers will have to will have
10:59
to come up with more transparency about what data set
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was used to train the model and what group of experts post
11:05
trained the model, right. Because model itself is just a
11:08
math, then you have a data set and then you have a group of
11:11
experts that do reinforced learning, etcetera, etcetera.
11:14
In the future, I would want the tech providers to be transparent
11:17
about what data set went in and who are these experts, quote UN
11:20
quote that trained it such that then I can transparently choose
11:24
which model I want to work with or not.
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But until then, users and my kids will have to learn to
11:31
unpack facts. I was quite impressed.
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But so my kids go to International School here in
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Amsterdam. A couple of years ago, my
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daughter was taking a history class and and I said, can I see
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a history book? I really want to see what
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they're teaching you, right? Because the history, you know,
11:46
it's, it depends who wrote the book.
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And she said, we don't have history book.
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I'm like, what do you mean? Like, how do you study history
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if you don't have a textbook? And she says the way they teach
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history in this International School in Netherlands is they on
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one day, they tell kids, look, there was 1812, the year 1812,
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there's this person Napoleon Bonaparte, and he attacked this
12:07
country by name Russia. Go and find out everything you
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can about it. And they just, and they just
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asked them to go and do the research.
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And then they spend a week kids doing their own research.
12:15
Nobody tells them how to do the research.
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Week later, kids come back to the classroom and one by one
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they stand up and they start telling the story that they've
12:22
researched. And very quickly, like 15
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minutes into it, kids started like looking at each other like
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why am I story different from your story and your story?
12:30
You know why our the outcomes of research came out quite
12:33
different And very quickly this class turns into not learning
12:38
the facts or not learning the definition of truth of what
12:41
happened, but learning how do we live in a society when we have 5
12:44
people and five people have a different versions of what
12:47
happened. So the teaching history becomes
12:49
less about fact and it's more about how do I live in this very
12:53
complex society and and navigate the complexity and different
12:57
convictions. That was a big aha moment, big
12:59
unlock for me. It's like I need to teach my
13:01
kids in the world where access to knowledge and quote UN quote,
13:06
post synthesized point of view is easily accessible.
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You will have to like society is already highly fragmented.
13:13
It's going to be even more fragmented.
13:14
I think in the future, it's going to be critical human skill
13:17
to live in a society and, and and connect the dots and and try
13:21
to reconcile while why different people have different point of
13:25
views. So AI can take us up to a
13:27
certain point. It's it's a tool, but this this
13:30
human skill of navigating the complexity, connecting the dots
13:35
and helping people align on on the intent.
13:38
It's going to be highly, highly human.
13:40
So that's what I'm investing in. And if you turn this into games,
13:43
obviously it's, it's much less boring like than what I'm
13:46
telling you now. But when we play with kids, but
13:49
asking critical questions, double checking, even like even
13:53
prompting, you know, you prompt something that it gives you an
13:56
outcome and then next prompt is like, now give me quite the
14:00
opposite point of view in debate with yourself, like as an as a
14:03
user, it's a quite interesting mental exercise where you force
14:06
yourself to read to opposing point of views and then work
14:11
through the synthesis. And that way AI becomes the
14:13
assistant for your thinking rather than a driver.
14:16
And you've now shared with us of how you approach it from your
14:21
perspective. How do your children perceive
14:24
it? Like what do they reflect with
14:26
you upon? How do they circle back their
14:29
experiences using AI, not only probably in their learning and
14:35
like also personality development journey, but for
14:37
themselves particularly? I love it.
14:40
I mean, the fact that they well, first of all, no, hold on, they
14:43
love it. I'm sure they're going to be
14:44
listening to this podcast. So they come to Jesus moment
14:47
more often than not, the response is, oh, no, again,
14:52
we're going into this lessons learned, blah, blah, blah type
14:54
stuff from dad so that that that's there and I'm trying to
14:57
navigate how do I not become a boring dad that like tries to
15:00
get the piece of wisdom out of every conversation.
15:03
But the fact that they do have cell phones and I know there's
15:06
like the parents split on these opinions and whether you should
15:10
or should not give device to your kids.
15:11
All of my 4 kids other than 8 year old, so 8 year old doesn't,
15:14
but all other kids cut the devices at the age of 10 or so.
15:19
And the idea is like I want them to have, I want them to be able
15:22
to Fact Check and to confirm and go in and have their own develop
15:27
their own patterns of finding answers and not always rely on
15:31
what dad says or what mom says, etcetera.
15:33
And it's very interesting. So my 13 year old son, three
15:37
years ago, when he was 10, he said that I want to to code.
15:40
I'm like, yes, awesome, great. I'm going to hire you a great
15:43
teacher. You're going to be a great
15:44
coder. He's like, no, no, no, I don't
15:46
need a teacher. And I'm like, what do you mean?
15:48
He's like dad, there's YouTube, right?
15:49
Like so in like in two days, he learned to he learned to how to
15:54
write games in Python from YouTube, which was pretty cool.
15:57
And then he goes from like one game to another.
15:59
He starts iterating. And then I said, you're really
16:01
good at this, let me hire somebody who can make you even
16:04
better. He's like, look, and this is
16:05
this was another aha moment for me.
16:07
And I think, I don't know if it's my kids.
16:08
So it's a generational thing. But my son said, if you hire me
16:11
somebody, I will learn to think how that person thinks.
16:15
If I go to YouTube, I listen to 15 bloggers, I read 15 different
16:19
things. I pick and choose what I like
16:21
and I compose my own learning path.
16:23
So I get to the outcome in my own way, in my own mental modes
16:27
rather than learning how other people think.
16:30
So for me, I mean, that's giving kids, giving kids curiosity.
16:35
This, it's a fundamental thing that's they're, they're curious
16:38
and then given them access to, to the tools.
16:42
It's super cool. It's just it's a super cool to
16:44
see how they come up with their own ways of learning, Which then
16:49
brings us to a separate topic, whether our educational system
16:51
is equipped to support that, that level of open endedness.
16:57
That is actually the connect that I wanted to draw to our
17:02
jobs or like the professional environment.
17:05
Because for me, there's the statement, we don't hire juniors
17:08
anymore because like we also need some more senior ones that
17:11
can now delegate or orchestrate or whatever.
17:14
And I have the hypothesis and maybe it's, it's going to prove
17:18
me wrong, but I do think it's not the right approach because
17:21
what you just described with your children having curiosity,
17:24
being able to solve things differently is a real addition
17:28
to, to teams. And it's also adding to like
17:32
heterogeneous collaboration. So I'm actually also looking
17:36
into the way of how these additional skill sets can be
17:39
built up into collaboration. However, our juniors coming
17:42
directly from universities, they are are sometimes differently
17:47
approached and trained of how they're thinking.
17:49
Also their ways of performance has been elaborated.
17:54
So bridging that from the university, like ending
17:58
university and entering the kind of like new ways of working is
18:01
something that requires also some sort of different kind of
18:04
leadership. So that is quite now the broad
18:07
aspects to it. But I did want to look into it
18:10
with you from a university like systems perspective, what would
18:13
be required different then also enabling like juniors in order
18:17
to be more curious and challenge existing processes And then from
18:21
a leadership perspective of what is required from leaders to have
18:25
this oversight into teams to bring those capabilities
18:29
together? Yeah, that's, that's a billion
18:32
dollar question. So let's let's take it in 1-2
18:35
steps. So #1 if you go back to the
18:38
technology again, the role of technology of AI and I, I live
18:42
in the world where I, I want human to always be in the loop,
18:45
like I always, I want the human to be responsible for the
18:48
decisions. I, I see AI an agent as
18:51
assistants, as an accelerators of the how, but it's always the
18:55
human that decides what we do and why we do.
18:59
And at the end of the day, there's got to be a human who
19:01
takes responsibility or accountability for the decision,
19:03
right? If, if AI helps a medical
19:06
profession to write a, a, a diagnosis, that's fine, but
19:09
there's got to be a human who takes responsibility for the
19:11
final yes or no. If the agentic system reviews
19:15
the mortgage application, there's got to be still a human
19:18
who says yes, yes or no. So there's got to be a human
19:21
person that not only takes responsibility, but also designs
19:24
the system so the system achieves the desired outcome.
19:28
That's so that's number one. Now, if I if I need a human who
19:32
designs the system, we'll go back to my definition of trust.
19:36
The first one is intent is like, what am I solving for?
19:38
What good looks like? What is the biggest?
19:41
What is the final outcome I'm building the system for?
19:44
And that is the skill that universities need to teach.
19:48
Historically, universities that I've I've been to and to the
19:51
best of my knowledge, the domain expertise that as we prepare our
19:55
kids are too narrow like we've we're building or educational
19:59
system teaches kids to be subject matter experts in small
20:04
boxes. So they can fit a job in a team,
20:08
in a function in a large organization.
20:10
And that says the whole model was designed in 20th century,
20:14
right? In the future world, knowledge
20:16
workers will be orchestrators of of the system.
20:20
So the knowledge worker will need to say, I have all these
20:22
tools, models, agentic platforms and orchestration layers.
20:26
I can orchestrate the work, but I need to know what I'm building
20:29
for in that way. The level of expertise needs to
20:32
be much broader. So I expect the universities to
20:34
respond to this and say we're not like the faculties or
20:38
schools or or departments or how do they call them colleges and
20:41
universities. They will have to broaden up the
20:44
breadth of knowledge and skills that they're teaching.
20:46
So it doesn't make sense such that people will be able to in a
20:51
much smaller teams to design the holistic end to end systems,
20:55
rather than you would have to like put 15 different very
20:58
narrow, very deep subject matter experts to say, now you're
21:01
collectively designing a system which is super complex to do.
21:03
We just started this conversation from from the
21:05
beginning. So, so education system I
21:07
believe need to change very rapidly and expand the the T
21:11
shape like the vertical T of of the of students that they're
21:16
graduating and producing. It's trading on that.
21:19
I want to share a hypothesis with you and I would love your
21:23
perspective on it in terms of collaboration models of the
21:26
future or let's call them operating models.
21:28
But I do think that future teams are are smaller than the ones
21:33
that we have currently and they will be cross functional.
21:36
So in a lot of organizations we have full sets shaped or
21:41
allocated towards projects outcomes.
21:44
And I do think that we need some sort of speedboat teams that are
21:50
able to drive into the direction of the larger perspectives and
21:55
also like the overarching value chain of an operating model such
21:59
as as an organization, how do using that?
22:02
Legacy companies, large companies in my point of view,
22:05
will struggle with us a lot and we will see companies.
22:08
Let me make a statement and then I'll rationalize.
22:10
I'll explain why I believe so. Legacy companies will be super
22:13
slow to respond to that trend, and there will be younger, more
22:16
nimble companies that don't have legacy org structures, legacy
22:21
egos, legacy processes, and ways of working that they have to
22:24
comply with. Sorry, but in general you would
22:26
agree with the 100? Percent agree that's the
22:28
decision. But you, you said something
22:30
interesting in your, in your statement, you said cross
22:32
functional. I, I believe that the definition
22:35
of functions will change in the future.
22:37
I would even like, I wouldn't call it cross functional.
22:40
I would call it outcome based, right, because the way the
22:44
functions are built like so I build the product, marketing,
22:47
distributed sell, sell sales, sales at finance collects the
22:51
cash. This is how we designed the
22:53
assembly process in 20th century and that's how we designed
22:56
function. And now marketing is like 15
22:58
different marketing and sales, different stages of sales in the
23:01
future. You're not going to say how do I
23:03
put cross functional team? What you're going to say, how do
23:06
I get to this outcome with the least amount of people involved
23:10
in the least amount of handovers And I don't even care what
23:13
function they sit in. I just need to work backwards
23:15
from the outcome. But today the outcome is defined
23:19
by my job description. My job description is this.
23:21
This is my outcome. This is what I do.
23:23
I'm the best designer. I do the best pixel perfect
23:26
designs. Then I hand it over to somebody
23:28
else. I am the best UX researcher.
23:30
I produce the best UX research, etcetera, etcetera.
23:32
That's how we define outcomes. In the future, what you're
23:35
saying, the speedboats will, will crush the walls between
23:38
this job descriptions and I'll say, who cares about this
23:42
intermediate outcomes. What we care about is the
23:44
product is in the market, the users love it and we're
23:46
collecting cash. So let's work from that outcome
23:49
and work backwards into what it will take to to achieve this in
23:53
the future. So 100% agree that this is where
23:55
the puck is skating. And large organizations should
23:58
be asking the question. If they're not already asking
24:01
the question, they're already too late.
24:02
And then the punchline is why this going to be so difficult is
24:06
because people have egos. People have, if I am an expert,
24:11
I went to school, I paid $300,000 for my college.
24:14
I have a diploma in this space. I worked there for 15 years.
24:17
I told my family that I'm the best at XYZ.
24:20
My kids know me as the best at XYZ.
24:23
I write blogs about this. I'm on the stage, I'm speaking,
24:25
I'm the best person in XYZ and now you're my boss and you're
24:29
telling me saying gusha, you know what, this XYZ not relevant
24:32
anymore. Actually you need to shift to
24:34
the right. This is a a huge alter ego
24:38
traces for individuals like a lot of people like
24:40
subconsciously respond to that very defensively say no, no, no,
24:42
there's like myself worth myself value is attached to being the
24:47
best artist in this XYZ thing, and now you're telling me that
24:51
XYZ is not the thing. Now you have to shift to the
24:53
right. So and now you multiply that by
24:55
you know, 10,000 people in the average fortune, whatever 500
24:59
company. It's super.
25:00
It's the change transformation is human and humans.
25:04
And I understand that by the way, like I'm not very, I'm not
25:06
judge mental about this at all. Like I, I think this will be a
25:09
big self identity crisis for a lot of knowledge workers, like
25:14
redefining what are they attaching their self value to?
25:18
And but the good ones will step out, the good ones will embrace
25:20
the good ones will see it as a huge growth opportunity and will
25:24
move fast. So I hope large organizations
25:26
recognize this and, and, and start thinking about first of
25:29
all, inflow of new talent. Like my advice would be one, one
25:33
thing is within your control, control the inflow of unit tone.
25:35
So the new, the hiring policies, they need to be rethought
25:40
considerably. And then internally there are a
25:42
bunch of techniques how you can, you know, create like sandbox
25:45
environment and like, you know, put people behind the Chinese,
25:49
Chinese walls, allow them to move fast, break things.
25:51
But we, I think we, it's going to, it's going to take a while.
25:54
It's going to take a while for, for organizations to change.
25:56
And by a while, I mean like years, it's 5-7 years.
26:00
We'll see. And coming back to the very
26:02
beginning of our conversation and your formula for trust now
26:06
knowing that we have, let's call them cross talent on teams and
26:10
that there is also some sort of ego identity attached to the way
26:14
of how they will be shaped in future, the trust aspect becomes
26:18
probably more more relevant, or at least that's what I'm
26:21
exploring also. But I'm hosting the podcast.
26:24
But at the same time, we face this tax celebration and
26:28
shifting identities in times of speed, velocity and so on, and
26:33
also needing to constantly upskill our capabilities.
26:39
Isn't that overwhelming? And if so, how would we handle
26:43
that as persons but also then as an organization?
26:47
100% it is overwhelming. There will be a little bit a lot
26:50
of anxiety on the market. That's why I'm saying it's going
26:52
to take years because you can't hit the button reset on a 10,000
26:55
people organization, 100,000 it will take.
26:58
I don't have a golden recipe how to do this and gradually.
27:01
But what is clear that organizations need to think
27:04
about it and they need to have a strategy how to deal with this.
27:06
There's probably not the right answer, but they need to
27:08
recognize the depth of the problem and the complexity of
27:11
the problem and have a very gradual, you know, step by step,
27:15
face by face strategy, how we get from point A to point B.
27:19
What may throw a curveball into all of this is a competitive
27:22
environment, right? Because if I am incumbent and I
27:25
have my strategy and it implies that I'm moving gradually from
27:29
point A to point B / 5 years. And then there is a fast moving
27:32
speedboat comes from the left to the small AI native startup.
27:36
That disruption can 'cause leaders to rethink how fast they
27:40
need, they need to change. But it's also, it's also top
27:43
down on border bop like from, from leaders.
27:45
We can talk about it. We can say we have a strategy,
27:47
we have a plan. But it also a lot of owners also
27:50
sits with employees like the knowledge workers.
27:52
They're saying, like it's me, like if I want to stay
27:54
competitive for next 25 years, I have to do this.
27:57
I can't just take a passenger seat and, and rely on leaders to
28:00
come up with a plan. And I, I think your, your life
28:04
is in your hands and this is, you know, wealth of your kids,
28:08
they're on it. So I think a lot of knowledge
28:10
workers will have to realize how serious you said upscaling,
28:14
probably rescaling. That notion will be so big
28:18
opportunity for educational system to step in plenty of
28:21
resources. Now I'm thinking about whether
28:24
it's resources or it's mindset. That's an interesting question.
28:27
Maybe it's for a next podcast. It's like if I'm 37, I'm not 37,
28:31
but let's say I'm 37 and I'm offered this program for
28:35
rescaling, but I don't have a mindset for it.
28:37
Is mindset something that can be acquired in the middle of your
28:42
life? If I don't have a mindset for
28:43
that, I'm have a different path. There are so much routes that we
28:47
could now take because I would also be curious to hear who's
28:50
responsible for, you know, providing the opportunity to
28:53
rethink mindset as AD individual or the organization.
28:57
But I do want to briefly pick up on the curveballs because you
29:02
said like you threw in the incumbent ones.
29:05
Do you see any other curveballs that could be thrown into like
29:09
the way of as individuals but then also to organizations with
29:15
or without heritage? I mean the most imminent one I
29:18
think that's coming is I don't know if it's a curveball or not,
29:22
but I think everybody's talking about AI bubble overhyped
29:25
expectations, what it can, what it can do, whereas technology's
29:28
over mystified what's not. I think the next next several
29:32
years as knowledge workers and their leaders will drive their
29:37
own and team level adoption with AI that the level of proficiency
29:41
and familiarity with technology will increase and
29:44
correspondingly the level of mystification will will
29:47
decrease. So I think, I think what we will
29:49
see is a lot more like consistent understanding of what
29:54
AI cannot, cannot do for your business.
29:56
Like direction of travel is clear, like with with the models
29:59
and they're going to get better and bigger.
30:01
We're going to get more multi modality.
30:02
We're going to get the physical world, the general population,
30:05
knowledge workers will learn general principles.
30:07
Because right now I still don't believe people understand how a
30:10
A works the basic level. I mean, people know how to use
30:13
JDBT, but they don't know what's under the hood and how it works.
30:16
And therefore people sort of like tend to overestimate the
30:20
capability that is like I think was Bill Gates, right?
30:22
So like in short term, we overestimate and long term, we
30:24
underestimate the implications of technology.
30:27
So I would encourage everybody to invest their time to really
30:30
get, you know, hands dirty, sign up to tools, build your own
30:33
agentic flows, automations, help yourself increase your own
30:36
productivity. Like if you're using Chen GBT
30:38
right now, that's table stakes. That's not AI familiarity.
30:41
You need to start when I hire people, by the way, in my team,
30:45
I don't ask them whether you're familiar with AII asked them to
30:48
show me the latest genetic flow that they've built.
30:52
Like literally just on the call screen share, show me what
30:54
you've built. And it doesn't have to be work
30:56
related. It can be personally related.
30:58
And if if a person can't show, then that's the end of interview
31:02
because that's, that shows the mindset like where people are
31:05
theoretically curious, but not like really.
31:08
What's the last thing that you built?
31:10
I'm building a smart agentic system that it helps me to
31:14
manage the key professional relationships that I have.
31:17
So I don't want to call it CRM because CRM sounds like a
31:19
database. This is the proactive agentic
31:21
system that understands my business objectives, what I'm
31:26
trying to do. It understands where I am in
31:27
different relationships and it's it helps me to actively,
31:30
proactively manage the content, manage the touch points, manage
31:33
the relationships, etcetera. That's that's quite fun.
31:37
Also something that can be iterative and without ending
31:41
right, So it's probably. Exactly, Yeah.
31:44
And the first, first version will be super simple.
31:47
It's like Air Table plus Zapier plus your Gmail.
31:50
I mean, that's all you need. And then and then you start
31:52
building like connections to your sales force and gun calls
31:55
and your, you know, your calendar and things like that.
31:59
You can always at some point in time, you're probably will end
32:02
up buying a professional platform that is the same thing.
32:05
But just the fact that you can build these things in a no cold
32:08
way as a as a non-technical person is pretty cool.
32:11
And once knowledge workers who are not technical, once they
32:14
start putting their hands on these technologies, once they
32:16
start building, what the interesting thing will will
32:18
happen, They'll start being their curiosity will lead them
32:21
to ask questions. Why am I doing the way I'm doing
32:23
this? Is there a better way?
32:25
And you will start rethinking the way your work happens.
32:27
So you're not just going to be automating the steps as is, but
32:30
you'll be collapsing steps, you'll be skipping steps, you'll
32:33
be rethinking and and you'll become the orchestrator of your
32:36
own work. That is a really, really cool
32:38
sort of a byproduct of actually building something with your own
32:41
hands. On an organizational level,
32:44
who's the master responsible orchestrator and to orchestrate
32:49
or have the other persons collaborate on also like a
32:54
technological or knowledge sharing perspective if that is
32:58
something that's also, you know, continuously evolving.
33:02
The orchestrators might be different, but I, but I am, I am
33:05
convinced the tone from the top comes from the CEO.
33:08
Like the CEO has to come in and say, this is not optional, this
33:13
is mandatory. We're going there.
33:14
It's not like we're going to, I mean, OK, two months, we're
33:17
going to play around, we're going to give you tools, you
33:19
guys experiment, increase your own productivity.
33:22
But the tone from the top should be very, very mandated, I
33:25
believe and say, look, this is my organization, I'm responsible
33:29
for all of you and for the business model, I'm responsible
33:32
the shareholders to the board, etcetera.
33:34
I'm declaring this is not this is not optional.
33:36
This is mentor. We're moving with that speed and
33:38
everybody needs to hear that message from the top that it's
33:42
there's a sense of urgency and there's a sense of direction and
33:45
we're moving there. Now how it's been orchestrated
33:47
at the at the functional level. So there's different ways it's
33:52
top down, bottom up. Like we at Bureau, we do it
33:55
combination, we do a bottom up, we give a bunch of tools, people
33:58
experiment at the individual level, at the team level.
34:01
But we we did identify a series of use cases that are overflows
34:06
that are critical to the business end to end and those
34:09
are owned by senior leaders in the organization.
34:11
Again, they might come from the function, but as a owner of the
34:15
workflow end to end, they own the whole end to end.
34:18
So that that model can can differ company by company.
34:21
But I do believe that without clearly declared a mandate that
34:27
we're moving and we're moving with that urgency and beyond
34:30
that point is going to be non acceptable if you cannot work in
34:33
that way, like you cannot work for my company if you don't
34:36
behave like this after that day. Since we now come to the end of
34:41
our current episode, I do want to share some moments with you,
34:44
the so-called in between moments.
34:46
I have them with all my guests, so I also want to have them
34:49
together with you. And I want to start with one
34:52
question. What does trust feel to you
34:55
like? But trust feels.
34:56
I'll quote Satya Nadella on this one.
34:59
I really admire him as a leader. For him, trust is consistency
35:03
over time. And what does AI need more of?
35:07
AI needs more new ones and more contacts.
35:12
What is parenting in the age of AI to you?
35:16
Teaching kids to connect the dots and and synthesize opposing
35:20
point of views. And finally, what will the next
35:23
generation redefine? The next generation will
35:26
redefine how the work is done. Thank you for stepping into
35:29
those moments with me. And now thank you so much for
35:32
joining us, joining me on In Between Tech and Trust podcast
35:35
and also for sharing all your insights.
35:38
I loved it, but it was great. Thank you so much.
35:41
Appreciate it.