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- Up next is our panel,
Bringing Everyone Along
in the AI Revolution.
Please welcome to the stage
our panelists- Sebastian Niles,
President and Chief Legal
Officer at Salesforce.
Luana Genot, Executive Director
of the Identity Institute
of Brazil. Judith Spitz, founder
and CEO of Breakthrough Tech
and Moderator, Lashonda Anderson-Williams,
Chief Customer Officer,
Salesforce Industries.
Over to you, Lashonda.
Hello- Well, we're gonna continue
a fantastic conversation
and we can't start the Power
of AI without talking about
how do we bring everyone along
to participate in building the power
and the potential to make
our lives better, easier,
but more importantly make
this technology accessible.
So I wanted to say thank you
to my panelists here with me.
It's going to be a great conversation,
and I'm just going to jump
in and ask a question.
There's a motto
that says "Nothing about us without us"
or as FUBU would say, "For us,
by us" which I'm gonna sort
of take some liberty there,
but advocates all believe
that we need participation from
everyone to affect the type
of policies that will be put
in place when this technology
as it continues to be mainstream.
And we need to make sure that
we can have an open discussion
around how we design these technologies
for every person around the world.
And so I'd like to start
off by asking each of you,
what are the most pressing
inclusion challenges you think we
face today?
In ensuring that the
benefits are for everyone,
and making sure
that we don't deepen the
existing inequalities
that exist in how technology
has been designed to date.
So I'm gonna start with you, Judith.
First, give us your perspective.
- Well, thanks for the question.
It's great to be here.
Pardon my voice. I have a cold.
I want to start by saying I
think everybody believes here,
which is that the lack
of diversity in AI is actually dangerous.
The good news is that this is
a problem of our own making,
and therefore it's a
problem that we can solve.
There is no shortage of diverse
talent, in particular women,
including women of color, who are trying
to get a foothold in the
AI and the tech industry.
The data,
however, is that the
vast majority of those
underrepresented
students, 92% of the women
and 97% of the women of color
who are in college
studying tech today, trying
to get into those careers,
are attending colleges
outside of the top 20 universities.
And as a result, don't have
access to the privilege
to simply show what they're capable of.
And unfortunately, those
students, more often than not,
end up overlooked and underemployed.
And that is a challenge
that we have to lean into.
- Wonderful. Ana?
- Hi everyone. Hi. Is it
- On?
- Hello. Can you hear me? Hi.
Hi. Can you hear me?
- No. Hi. Let me see.
Yeah, I let you borrow this
one that's attached to me.
So, hey. Hey. Can't do that. Let's see.
- Yeah, maybe not
- See testing.
- Have a mic runner? No, no. Okay.
Mic runner. You're gonna come in,
- Right?
- Testing.
- All right. There you go.
That happens. So yeah, I'm
really glad to be here.
First of all, bringing inclusion
and colors to this amazing
table all the way from Rio de
Janeiro, Brazil.
- Yes.
- Woo. Yeah.
So for me, the motto,
nothing about us without
us is exactly this.
We need to be more
intentional, bringing voices
that are underrepresented and
marginalized to the table.
Because even if we are in the AI era,
we can not delegate intentionality.
And I thank Salesforce to
being very intentional,
bringing me here, because usually
those DEI discussions are very US centered
and they are very, you know,
pretty much the same people
discussing the same things,
which is very important,
don't take me wrong,
but we need to push the boundaries.
And I think the most
pressing issues now is like,
how can we push the boundaries?
How can we challenge
ourselves to go further
and invite those who are not in the table
to talk about the things that
are urgent in their context?
So I came from Brazil,
and in Brazil there is a
huge lack of infrastructure.
How can we talk about AI
without having the real
infrastructure about this?
How can we talk about
AI without electricity?
And we need to involve a
lot of different actors
to push the boundaries further
and to scale this
conversation beyond the US.
I also as a CEO of an organization
that I founded eight years ago.
I'm a CEO of Identity Institute,
Instituto Identidades do Brasil
So basically we recognize
that marginalized
and underrepresented
identities have limited access
to opportunities, to
certain opportunities.
It means that we know
exactly how is a CEO,
how, how A CEO looks like
usually in Latin America is a
white person, even if we are
the majority there in Brazil,
black and indigenous people
are three times bigger,
bigger population than a white population.
So we have three times more black
and indigenous people than
we have here in the US.
And we don't, we are not
represented in this kind
of conversation, not even Brazil.
So how can we actually
push the boundaries further
and to make marginalized
identities more connected?
And we've been actually
trying to, you know, as a,
as a pressing issue, we're trying
to disseminate more racial
and gender literacy, especially
for white decision makers,
because those are the ones who
deny that there is no racism
or this is not a priority
for the business.
And we try to push the boundaries
and say, this is a priority,
and now we can scale
this conversation with AI
and make this a more global
conversation for real. Thank
- You.
Wonderful.
- Sebastian?
Thank you. I'm really delighted to be here
as part of this discussion.
Look, I think the question
you pose is very serious
and significant, right?
You know, what are some
of the pressing challenges
to enable us to have an AI
future that's very inclusive.
Versus one deepening inequalities.
And I suppose I come at
that in a couple ways.
Look, first, the world that
we live in today is the world
that we collectively have created, right?
Whether deliberately or inadvertently
or, you know, for various kind of reasons.
I think though that is a deeply,
there's an optimistic element
there, which is that means,
okay, well the AI powered
agent first type
of world that is on the horizon
or that we're building, you
know, right now can be
A world and a future that features
where we've learned from
the lessons of the past
and where we've become very
deliberate and intentional
and conscious about these
types of, you know, issues.
You know, I think second, you
know, that's a,
the powerful quote, like
nothing about us
or for us without us raises
the following practical
question, which is on the
without us point, when? You see,
do you incorporate all
inclusive sort of perspectives
and engagement upfront, proactively?
Do you bring folks together along the way
or do you bring folks
together as an afterthought?
And I believe this is also
just goes to how, you know,
we think about trust, right?
So if you think about putting
trust at the center, a trust,
first motion around these
issues is similarly with trust.
Is trust upfront?
Is it something along the way
or is it sort
of as an afterthought?
And so when we think of kind
of going forward when it,
whether it's trust, whether
it's about inclusion,
whether it's about, you
know, sort of inequality,
I think we have to be also very practical.
And I think here about historical
digital divides, right?
And one of the things we think
about the digital divides
and different activities, you
know, I've been involved in
Salesforce, been involved in
other, you know, companies
and governments, is about
connecting the unconnected, right?
Let's get people connected
to the technology.
The, the challenge I always
find with that though, is
that at best it's an incomplete solution.
Why? Because, okay, let's assume
we achieve the incredible,
you know, what's on the horizon
of connecting the unconnected.
Okay, well then what? what happens then?
And I think when it comes to AI
and technology more broadly,
the, what happens then has
to be what are we doing now
in the following way, right?
How do we make this empowering?
How do you enable people to know
that this is technology they
can use, they can be part of,
they can define, rather than
it being something that happens
to the community, right?
The locality, the country, you know,
the demographic, you know, and the like.
And that's where I think whether
it's, you know, upskilling,
reskilling, new skilling, right?
Whether it's, you know, online
or, you know, in-person
training platforms like we have,
you know, sort of a Trailhead
or just, you know, collectively
the private sector,
civil society, and
governments coming together
to really focus on how do
we bring everyone along so
that this technology is
just really accessible
and empowering and indeed even easy.
- Well, I want to kind
of pull on that thread
and Luana, I'm gonna go to you.
because what you just
talked about, Sebastian,
was really about being intentional.
You talked about timing, but
it really means all of us have
to be inspired about the role we play
and how we shape this technology.
And the moment is now we don't
wait until after the fact.
So Luana, I wanna ask you a question.
How can we empower
and inspire underrepresented groups
to participate in the AI revolution?
And what, maybe give
us an specific example
that you've seen work and that speaks to
how do we actually make this
real for everyday people,
the students, organizations,
and communities to participate.
But I really wanna hone in on
sort of pulling on the thread
of empowering and inspiring people
to participate and act now.
- Yeah, Lashonda, we
were just talking about this
a few minutes ago.
And I'm a person from a very
underrepresented group in Brazil.
I'm not, I'm not a
technologist by background.
And I'm jumping in this
conversation about AI
because I'm enthusiastic,
because I think in this time in history,
AI made it possible
to make this conversation about racial
and gender literacy is scalable
and easier for everyone.
And obviously,
and when I say every,
every one please look at that
with those exceptions that,
as I was mentioning about
infrastructure, we still
need to work a lot on
so many different issues,
especially in the global south
and so many other regions.
But I think it's a new
momentum in history
where we are more invited
and we need to either invite
ourselves to the table
or take the opportunity
of events like that,
that invite us to be here.
And I've been working with
so many different actors in
Brazil, like the government,
or even across like 1 million
employers, helping them
to basically craft affirmative
actions there or schools.
And what we, we saw, for example,
was like professors in Brazil
that were very afraid of
the drop off, the high
drop off rates of students.
And they found out that AI
could help bringing more
representativity to their
class, to the class in terms
of examples they would use.
And by saying that, I mean, for
example, a physics professor
who never thought about
inclusion in his class,
and now he can ask our AI
for example, Debbie, like, oh,
how can I actually be more inclusive
and bring more, more
representativity to my class,
my physics class?
So it's not only about
the history professor
or all the professors
who are actually involved
more in the topic
of gender or race.
So we are trying to push
the boundaries and,
and talk to more people
beyond our echo chamber
because we need to make
this topic more scalable
and more accessible for everyone.
And for example,
another example is when
we are talking about this,
for instance, in the
labor market, how many
of us had the difficulty of
negotiation, for example,
to negotiate the next salary
or the next job position
or something like that.
So AI can be a very customized tool
to help marginalized communities
and say, Hey, are you
still in this position?
How about you negotiate the
next step for your career?
So we are
training our AI to be this tool
to push those marginalized groups further
and to ask them to help, to ask questions
that they sometimes are afraid of.
Also, another example could
be a white decision maker
that's afraid of talking
about their fears in terms
of asking difficult questions.
I don't know, I don't know
what's, what races, I don't want
to be dumb in front
of the other colleagues
talking about this question,
which is, you know,
some people can judge me
and then we can build a
safe space for this person
to actually, this person
can actually ask any sort
of question in a very private space.
So it helps us to,
to build this allyship
in a more secure way
so people are not afraid
of being canceled.
So those are multiple ways we can use.
But also, you know, in
terms of reducing the times
of trials, in terms of criminal
trials in Brazil, massive,
you know, the number
of cases where black
and indigenous people
are misidentified by,
by criminal trials, for example.
So we've been seeing not only with us,
but in other cases in Brazil
and Latin America where AI can
be very, pretty much a tool
for underrepresented communities.
So I'm enthusiastic with that.
- For a non technologist,
you've got some phenomenal
ideas on how technology
can play a pretty important role.
- I have a lot of needs,
so the need make us
to use the technology.
- Absolutely. Well, I'm
inspired, I'm going to come to you,
Judith, because I kind of
want to counter that with all
of the potential and opportunity
that Luana just talked about.
You've talked, you've sort of
talked about gender and equity
and tech and the issue of
having this broken supply chain
where there's all these needs,
but there's not enough talent
to serve the needs, especially
to represent the communities
that are here in this audience
and viewing and live and that
represent our communities.
Tell us more when you,
what you mean about broken supply chain
and what does that actually then look like
to bring everyone along
this new AI revolution?
- Yeah, so I mean, I'm listening to all
of the incredible
opportunities, the opportunities
to uplift society,
the concerns about
endangering it and so on.
And I think about all of that.
I was listening to your
comment about the when,
because what I talk about is
we can wring our hands all day
long about whether this
technology is really going to
help or we have to be concerned about it.
And with all of the what
and the how and the when.
I think the first and most
important determinant of
that is the who.
- So who is in the
room that is number one,
pointing the technology at
society's biggest concerns
and asking those hard questions,
excuse me, about fairness
and ethics and bias and so on.
There's no shortage of companies out there
that say they want a more
diverse workforce in general.
And in AI in particular,
if everybody doesn't know
the stats, the numbers
of diversity in AI are
as bad, if not worse
as they've been in tech all these years.
In particular, with respect
to gender diversity, 23%
of today's work, AI workforce
or women in terms of women of color,
we're talking about single digits.
Okay? So you have industry on
the demand side saying they're
looking for this talent,
and yet they quote unquote, can't find it.
So I go back to the statistic
I mentioned earlier.
There is what I think describe
as a feeding frenzy looking
for AI talent at the
quote unquote "top 25"
universities in this country.
The problem is that that
is a pool about this big.
We're talking about in the hundreds
and 90 plus percent a
pool, this big of talent
that actually is studying tech trying
to get a foothold in the tech industry,
and they're being overlooked.
So that's what I describe
as a broken supply chain.
Why is that happening?
First of all, at its core, these students
who have all the potential
intellectual chops
and the grit to contribute,
what they don't have is
the privileged access
to the opportunity to simply
show what they're capable of.
We talked about democratizing
all kinds of access.
These students don't have the
access to simply demonstrate
that they can compete.
Now, how could that be?
First of all, in terms
of academic resources
to learn the technical skills,
there actually is a shortage
of academic resources
that are held up in a small
number of universities.
So if you go to one of the
other 1300 schools in this
country, you may not even
have access to the coursework,
much less the academic support.
But the second, and equally
as important, especially
for all the industry folks
here, is hiring managers tell us
that what they're looking
for on resumes is evidence
that the candidate can
build real stuff, okay?
What I call the resume gold
of experiential learning
that more privileged students get
because they have the luxury of free time
to do unpaid activities.
And because of their opportunity
to get their foot in the
door in industry projects
because of either the network
or social capital that their universities,
or quite frankly, their families have.
So these, the rest of these
students end up overlooked.
We have sort of looked at
each one of those problems.
And in the organization
that I founded and run
after, by the way, a very
long 30 year corporate career,
believe it or not, that started in ai.
So anybody who thinks that
AI just came on the scene,
we know that's not true.
And we said, okay, how
are we going to close
that opportunity gap for
those students simply so
that they can show what
they're capable of?
Just level the playing field.
Think of it as democratizing privileged
access to opportunity.
That's a mouthful.
I think the problem is in the
white space between industry
and academia, it requires intermediaries
that design and deliver
innovative programmatic bridges.
And that's what we do so quickly.
For example, we are working
with the more elite universities
around the country, forming an
instructional hub in which we
pay faculty
and PhD students to actually
teach a machine learning course
that we design, not to their students,
but to the ones we are
recruiting from hundreds
of universities across the country.
That's one. Two, we partner with hundreds
of industry players,
large, small, nonprofit
and so on to simply host
portfolio building projects.
We bring the students,
match them to industry,
and they get that resume credential.
That they need, professional
readiness training
so these students know how to show up
and importantly, a community, a community
that will number one lift as they climb
and will hopefully once
and for all change the
culture of the tech industry.
The important thing here is
that it can't be one and done.
This isn't a light lift.
These students need all of those
gaps filled.
We have over a thousand women
in our program from all across
the country, and 80%
of them are landing paid summer
tech internships or jobs.
This is up from a rate
from the schools, they go
to about 10%.
So we know this can work
and we know it can scale,
and we're simply leveling
the playing field.
So these students who
are knocking on the door
can get their foot in so they can show
what they're capable of.
- That is fantastic.
So this pipeline issue is really a myth.
It's about connecting. It's,
it's not about pipeline.
The talent is there, it's
just matching the talent
to where the opportunities are.
And so kudos to you and your
team for the work you're doing.
- Yeah.
- I'm gonna switch gears a little bit
and shift around some of
the conversation around AI
that comes in respect to compliance
and trust and privacy.
And so, Sebastian, this is for you
as AI is rapidly evolving, there appears
to be more legal concerns,
especially in areas like
data privacy and bias.
How does Salesforce balance innovating?
Which we're always on the
cusp of finding the thing
that is going to help transform
our customer experience
and building stronger customer trust.
But how do you, how does
Salesforce innovate with all
of these different legal
and regulatory frameworks
that are kind of being created
with AI in mind,
but ultimately it's gonna
be a critical component of
how the company is successful.
So can you share your perspective about
how Salesforce is leading in that way?
- Yeah, sure. You know, you,
you implicitly highlight a
number of trade-offs, right?
And how do you balance, you know,
these different sets of issues?
I think at Salesforce our philosophical,
but then you'll, as I
explained it a little bit more,
it's sort of deeply practical,
we think anyway, is that
if we choose as our
north star trust, Right?
One is a value, two
as an operating principle,
and three as a means
and a lens to assess this question of,
which sometimes I think is a
false dichotomy too, right?
Of innovation, you know,
versus, you know, compliance.
That what we have found to date,
and particularly as we drive
forward into this next era
of AI and agentic AI and, and, and,
and the like trusts provides the answer.
Because the answer is
responsible innovation,
where you bring in
and think about all the
different, is it legal issues?
Is it privacy issues?
Is it sort of inequality, you know,
issues very early on, right?
Into sort of the product
and solution development
sort of lifecycle,
but then especially in the area
of the feedback loops, right?
How are we learning
and almost co-creating
these technologies in
the future with the input
and partnership, right?
Whether it's, you know, our,
you know, tens of millions
of Trailblazers, you know,
worldwide, whether it's,
you know, the work that we're
actually doing in Brazil
with sort of vocational schools,
particularly focused on
marginalized, you know, communities
to, to upskill, to reskill, right?
To bring technology,
but most especially to get the
insights and inputs, right?
Sort of from all these
sort of various, you know,
communities, you know, worldwide.
Also, when I mentioned it being kind
of an operational point, is
when we think of, you know, AI
and agentic AI with our agent
Forest platform, when it comes
to these sort of sets of
issues, we actually think about
what are our guardrails, right?
What are the trusted guardrails
that we're going to have?
What's our governance right
around these sort of issues?
What does responsible governance
look like?
And then third, what are
the, what's the guidance
that we're going to try to give, right?
So guardrails, governance and guidance,
and this plays into our
acceptable use policies.
You know, it plays into
the choices we make,
you heard in the earlier panel, right?
That just because we can,
doesn't mean we should
But also helping to bring together
and sometimes inform
whether it's regulators,
whether it's civil society
groups, whether it's other sort
of various, you know,
sets of players about,
here's the whole set,
the menu of options here,
here are the ones that
maybe do put trust more sort
of at the forefront,
or where compliance can
be more of a baseline.
And then over time you end up figuring out
how might you be able to
exceed the expectations
of customers, of communities,
of the broader stakeholders so
that you truly have built
an ecosystem, right?
That's another concept
we heard earlier, right?
An ecosystem of trust, an
ecosystem of sustainability,
an ecosystem of customer
and stakeholder success.
An ecosystem of innovation,
an ecosystem of equality
in a way that is just deeply meaningful
and impactful to the stakeholders
who we should all be seeking to serve.
- I'm going to maybe ask a
follow up question to that,
because while that's the core of,
maybe the approach is also just
the business of being in AI,
how do organizations think
about staying competitive?
With that as a backdrop,
what do you advise
or what do you, you know,
provide maybe some advice on
how do you use that as a competitive
advantage to win in this race?
Because it's a tight race within a lot
of technology companies trying
to balance the innovation,
but staying true to their values
and then also understanding
that these frameworks are changing every
single day. It feels like
- That's right.
The, the pace velocity of change, right?
We've never seen it sort of this fast
or this deeper, this wide.
The only path to be
competitive is to treat
and embrace trust as
a core differentiator.
And very, very take that
very, very seriously
and come at that from the lens
of seeing across industries
and seeing across governments
and seeing across communities, right?
Where trust actually is, inspires
folks to want to co-create
and co-innovate with you.
Trust inspires customers
across industries to say, yes,
you should be our partner of choice
because you have thought
through these items, right?
With us. And that ultimately
trust ends up being that bond
where we can become more human, right?
Sort of in these, you know,
different sets of areas.
Or, you know, last week at
Salesforce we announced a new
accelerator program.
It's our agent force accelerator
for nonprofits, right?
Another sort of mission driven,
you know, organizations,
you know, one group
college possible, right?
So different folks, how do
you use AI and technology
and agents to make this journey, right?
Sort of better have people have
better outcomes at the end.
But really just more broadly,
the more that folks find,
use this technology, you know,
we have a term, you know,
called a hands in the soil, right?
And again, hopefully, you
know, all of, you'll be able
to know, build your first agent
or, you know, use your prompts in sort
of this specific very intentional way so
that everyone just sees how,
how much possibility is not just present,
but is inherent by humans
getting engaged on this
to define the future, right.
That we really want.
And then come up with even better
ideas than what we may have.
- Wonderful. I'm gonna ask my final
question to all three panelists.
And Judith, I'm going to start with you.
You've got an audience full
of Trailblazers and leaders
and luminaries and people
who are in the work today
building out this great new
innovation for their
communities and their customers
and maybe for their families.
What advice, one piece of
advice you would give anyone
who was ready to start
now giving the backdrop
of this conversation this afternoon?
- Okay, I'm gonna, I'm gonna twist your
question just a little bit.
Sure. But I'll be fast.
- For people trying
to get a foothold in this industry,
especially women in underserved
communities, number one,
start doing, stop wondering
if this can be possible
or that.
The tools are out there.
Just start doing. The more you use it,
the more you can say in interviews
that I did this, that, and the other.
Number two, especially
for the women out there,
being a great team player
doesn't mean being deferential.
Number three, be a great
storyteller, and especially on
a team, tell your own story.
Don't let other people
tell your story for you.
And last is always, always,
always lift as you climb.
Because then when you get to the top,
you'll have brought others like you along
and will be better for everyone.
- I have a feeling, I have a feeling,
you've said this before.
Great advice, Luana.
- Well, I think Judith did cover it all,
but yeah, absolutely.
But two things I would say
also from my global south
perspective, I would say
highlighting what Judith just said is
that if you don't feel that
you're invited to this table,
invite yourself to be here.
Because sometimes I, you
know, I talk to a lot of,
from President Lula to other people,
and then we think, oh, maybe
we're not invited to this kind
of forum or to this kind of conversation.
That's not the moment. Not
now. Maybe, maybe after.
No, we need actually to
shift this cultural mindset
and say, that's now,
and if they don't invite me,
I'll invite myself to be here.
- Basically, we try, we
are trying to basically
to hack the system in a positive way
because it's not always
that underrepresented
and marginalized groups from
different parts of the globe.
If you are invited to the global north
and you know, there are so many
barriers, language barriers.
So I'm here with 15 hours of jet lag
and barriers, various barriers,
but we cannot only think about barriers.
We need to think, okay,
I'm gonna go, I'm here.
We are, we are building bridges among us.
And that's important and
intentionality.
I would think that's the
second key in important
thing for this topic.
We need to be very intentional in
how we train our AI models.
How can we build trust,
especially in an era in the
where we are facing the lack of trust.
You guys are facing
election tomorrow, right?
So good luck
and it, this is important issue, issue,
an important thing we
need to discuss right now.
The lack of trust and how
can we actually build trust?
How can we build
intentionality regardless of
who will win tomorrow?
We need to be very intentional
in tackling this issue,
not only as a, you know, beyond
the backlashes, beyond like,
you know, the fashion or we
need just to go for further
and to actually say, oh, we want
to serve under represented communities.
Go for it. Yes. Regardless
of the context. So go for it.
And I think that's very important.
And in our institution we
say that more than say no
to racism, we say yes to racial equality.
It's a statement. It's saying
that everyone is accountable
for equality.
Everyone is responsible.
It's not only for black
or indigenous folks, it's for everybody.
And that's why I invited
everybody to say yes,
to racial equality.
Sim à igualdade racial
Can I hear that?
- No, let's say, let's say, let's do
that two in two different
languages, right?
Yes to racial equality.
- Yes to racial equality
- Sim à igualdade racial.
- Sim à igualdade racial.
- Ah, they were pretty
good. Awesome. Come to
Brazil and learn that.
Yeah. Let's, let's build this bridge.
- Thank you. And Sebastian,
you'll close this out.
- No, not so much advice,
but just I think, you know,
quick perspectives. Really starting with
what you said earlier, which is, you know,
I have many needs, right?
We have many needs. The world
has, you know, many needs.
And you know, like at Salesforce
we have our weekly internal
AI summits, right?
And I, you know,
participate in all of those.
And it's like the biggest so exciting
computer science project.
And yet, right?
And so as I, as I discussed
with my three daughters
around AI is, ultimately, it
can't be AI for AI's sake.
It has to be AI
and technology for beneficial
outcomes to meet the needs
that we see all around
them, all around us.
You know, as I also sort of
say to my daughters, often
I learn more from them, right?
Than they may think I'm learning
or like they're learning from
me and I really mean that.
And so this element of like,
you know, find your own power,
know your influence, right?
Be curious, be engaged,
and you know, over the course,
you know, wherever you are,
you know, in your journey,
whether you've been a
professional, you know, for
30, 40, 50 years, right?
So already, or if you're
kind of earlier on, is
that really figuring out, have
that self-awareness, be open
to feedback, but just know
the opportunity going forward
to leverage technology
and AI to make a tremendous
difference, to meet the needs
of the world, of families,
of communities, of the globe.
It is going to be the most
significant decade ahead of us,
and we have to define what
that ought to look like.
- Wonderful. Well thank
you to my panelists
for this fantastic conversation.
- Thank you Sebastian,
Luana, Judith, and Lashonda.
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