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Critical Moment How Can We Make AI Inclusive from Inception
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00:00Wow, this is loud.
00:02In just two years,
00:06artificial intelligence has gone from being an abstract technological promise
00:11to being used at scale in our daily lives, both professionally and personally.
00:17Algorithms and conversional robots
00:22are revolutionizing fields such as medical research,
00:27logistic flows, recruitment processes,
00:30even the educational choices of our children,
00:34and our internet daily searches.
00:38In other words, artificial intelligence is part of our understanding
00:43of today's world and of our decision-making, big or small.
00:49But here is the thing.
00:5188% of people who design algorithms are men.
00:5896% of deepfake are fake pornographic images of women.
01:06If you ask an AI tool to design or to represent a profession
01:16without saying if it's a male or a woman,
01:21you will get a male doctor, a female nurse, a male CEO, and a female secretary.
01:31AI is not sexist as such,
01:33but it's driven by humans and data that reflects our society
01:38in all its imperfections.
01:41Actually, those technologies simply follow rules and codes chosen by humans.
01:50Algorithms are therefore very good students.
01:53But who are the teachers?
01:56What are their curriculum?
01:58What ethical, moral, or legal rules do they follow?
02:04If artificial intelligence is to be a real source of progress,
02:10we must ensure at all costs
02:13that it would not contribute in promoting, generating,
02:18emphasizing, amplifying gender inequalities.
02:23We need to encourage more women
02:26to learn AI professions and technology.
02:29We must work to integrate diversity in data models.
02:35We need to include women in decision on AI government
02:39in the UN, in the G7,
02:42and of course, more recently, in the AI Act European Pact.
02:47Since 2005, we at the Women's Forum
02:51have been raising women's voices
02:53to create change in the same field sector.
02:59So, integrating diversity
03:03is not just a question of representation.
03:07It's giving its full potential
03:10to augmented intelligence
03:12at the service of our curiosity,
03:16our creativity,
03:17our critical thinking.
03:19I'm very happy to welcome on stage,
03:22to moderate this panel session,
03:25Claudine Schmuck from Global Contact.
03:30And also,
03:34to introduce our partners and friends,
03:37Barbara Sosa from Senior Vice President,
03:42Head of Consumer Products at MasterCard,
03:45Shelley McKinley, Chief Legal Officer at The Club,
03:50and of Stéphanie Delesse, CEO and Founder at Volubilea.
03:55The stage is yours.
03:58Thanks a lot, Isabelle,
04:00and welcome to all of you
04:02to enter this session on this really important topic.
04:08We'll actually jump right away
04:10in the pool and in a question.
04:13So, I'll turn to Barbara.
04:16And Barbara, the use of generative AI
04:19is, as you know, very powerful,
04:21as it enables less subjective decision-making process, right?
04:26Yet, no well-monitored,
04:28if it's not well-monitored,
04:29it reproduces bias,
04:31and we all know about those issues, right?
04:35So, harnessing the enormous transformative power of AI
04:39requires addressing the good balance, right?
04:43And make the best out of it, right?
04:44Right.
04:45So, MasterCard has been at the forefront of businesses,
04:49developing policies on this topic,
04:52with the presentation of its data,
04:54responsible principles,
04:57as of, actually, 2019.
05:00And it hasn't stopped working on this since then, right?
05:05Now, can you explain to us
05:06how you define those personal data rights
05:11and how you secure their protection for your customers,
05:16all of us right here, right?
05:18Yeah.
05:19First of all, good morning, everyone.
05:21I'm delighted to be today here,
05:25and thank you for the first question
05:27that gave me the opportunity to open this debate.
05:31At MasterCard,
05:33we recognize the pivotal role of artificial intelligence,
05:39and let me say that in this technology revolution,
05:44we are not only the participant,
05:47I let say that we are the architect, right?
05:51And I don't know how many of you know this,
05:54but we have over 20 years,
05:59so two decades, of expertise,
06:01and we use and we leverage artificial intelligence
06:05to make every digital transaction
06:09even secure, faster, right, smart, and personalized.
06:15So, to me, it's important to recognize
06:19that the artificial intelligence
06:21as any other tool, tech tool,
06:24you can use for good or not, right?
06:27Yeah, as always, right.
06:28It's nothing new.
06:29Nothing new.
06:30And when it is readable,
06:33when it's clear, transparent, and ethical,
06:37people trust it.
06:39And why I'm talking to you about this,
06:41and trust,
06:41because for MasterCard,
06:43I don't know how many of you
06:45would just give me the opportunity
06:46to remind who we are
06:48and what we do.
06:50We are a technology company, right,
06:54connecting through our network
06:56billions of consumer,
06:59financial institution,
07:01government,
07:01and merchant.
07:03So, people have to trust us.
07:05If we don't have this trust,
07:07we lose business.
07:08So, it's for AI,
07:10but it's for any tool
07:11that we develop and we use, okay?
07:16And so, for us,
07:17the only AI possible
07:19is a responsible AI.
07:22That's why, back to your question,
07:24we have created
07:26and we continue to work
07:28on a set,
07:29robust set of principles
07:32that hold us
07:34to the higher level
07:36of integrity, right?
07:38And that was to create
07:40this framework
07:42for responsible data innovation.
07:46And I want to list,
07:47to use some few of these principles
07:49because it is important.
07:51First of all,
07:51security and privacy, right?
07:54Security and privacy,
07:56we leverage the best-in-class process.
07:58to grant security and privacy.
08:01And on the personal data,
08:04what is important for us
08:05is stay personal, right?
08:08We say, you own it,
08:10we protect it.
08:11This is our philosophy.
08:13The second principle of data
08:15that we use
08:16is to be transparent.
08:19We want to make people aware
08:21on where we collect data,
08:24how we use data
08:25that we collect.
08:27and then, of course,
08:29there is the accountability
08:30that we use
08:31because we are in charge
08:33of this.
08:34There is the other element
08:36that is social impact.
08:38I will not spend time,
08:40you understand what does it mean?
08:42Innovation.
08:43And the last point
08:44I want to focus in
08:46is fairness.
08:49we work with intent
08:51to mitigate
08:53any bias
08:55we can have in data.
08:57Very important,
08:58as we know,
08:59in this topic.
08:59Of course.
09:00And so,
09:01a practical example
09:02that I want to share
09:04is what we have done
09:05back in 2019.
09:06with our AI
09:10governance model,
09:12right?
09:12So,
09:13what we did,
09:14this is a council
09:15that works internally
09:17to any activity.
09:20So,
09:20you mean that
09:20the AI governance council
09:22is actually
09:24controlling
09:25or looking at
09:26what comes
09:27from technicians
09:28on this topic?
09:29Yes.
09:30and we want
09:31to ensure
09:32that any activity
09:33of the company
09:34is in line,
09:35right?
09:36With this data principle.
09:37And so,
09:38this going
09:39beyond compliance.
09:41This
09:42really touch
09:43the way
09:44MasterCard
09:45intent data
09:46and technology.
09:48That's great
09:49because,
09:50indeed,
09:51it's very important
09:51that trust remains
09:53and that it remains
09:54only if,
09:55you know,
09:56protecting the consumer.
09:57As you said,
09:57we own our data,
09:59which is important.
10:00and that's fair.
10:02These are
10:02absolutely crucial.
10:05So,
10:05let me,
10:06perhaps,
10:07just one quick word
10:08if you allow me
10:09to,
10:10one last quick word
10:11to you
10:13regarding
10:14the fact
10:15that you,
10:16you highlight
10:17the fact
10:17that
10:17interiordisciplinary
10:18policies are important.
10:20Yeah.
10:20And do you want
10:21to explain
10:22a few seconds
10:23because we're
10:24running out of time?
10:24on that.
10:25We combine
10:26the how
10:27that is
10:28leveraged
10:29by the
10:31engineers,
10:32by the product
10:33developer,
10:34what the
10:35what if,
10:36right,
10:37and why
10:38we are doing
10:39that.
10:39It's very important
10:40that there is
10:41this sort
10:42of agreement
10:43internally
10:44between the
10:45different function
10:46to advance
10:49in that topic.
10:51And again,
10:52I want just
10:52to pass
10:52the last message.
10:53This is for AI,
10:55but this is for
10:56master case
10:56for any
10:57digital tool.
10:59Excellent.
11:00And if you have time,
11:01we'll go back to that.
11:02But now I'm
11:03turning on to
11:04Shelley McKinley
11:05from GitHub.
11:06We're so excited
11:08to have you on board
11:09because we know
11:09that GitHub
11:10is at the forefront
11:11of so many things
11:12right now,
11:13and particularly
11:14now.
11:16Three years ago,
11:17actually,
11:17GitHub launched
11:18its AI developer
11:19tool,
11:21GitHub Copilot,
11:22to the community,
11:23which now
11:23is over
11:24100 million,
11:25right?
11:26Correct?
11:27The GitHub
11:27community
11:28is over
11:28100 million
11:29developers now.
11:30so it's huge.
11:31So as has been
11:33the case
11:33with many
11:34new AI tools,
11:36some shared
11:38fear,
11:39uncertainty,
11:40you know,
11:40what's going
11:41to happen
11:41to software
11:42development
11:42and so forth.
11:43And then
11:44in those times,
11:45you've noted
11:45in an interview
11:46that GitHub
11:46is trying
11:47to take
11:48a responsible
11:48approach
11:49to ensure
11:50meeting
11:50the needs
11:52of our
11:53community
11:53and developers,
11:54right?
11:55That's what
11:55you said
11:55in those days.
11:57So now,
11:57today,
11:58can you speak
11:58to GitHub's
11:59approach
12:00and its impact
12:01on the developer
12:02community
12:02when there is
12:04something very
12:05important
12:05which is just
12:06about to happen?
12:08There's always
12:09lots of important
12:09things happening
12:10at GitHub.
12:11So,
12:11hi,
12:11I'm Shelley McKinley,
12:13Chief Legal Officer
12:14of GitHub.
12:15Very happy
12:16to be with you
12:17here today.
12:18Just to sort
12:19of quickly double
12:20down on
12:20what we are,
12:21so we are
12:22a community
12:22of developers
12:24where developers
12:25collaborate
12:26to build
12:27software,
12:28meaning to build
12:29our digital future.
12:31Over 100 million
12:33developers
12:33on the platform
12:34today.
12:35So if you're
12:36here at Viva Tech,
12:37you're, of course,
12:37probably very
12:38interested in AI
12:39at least,
12:39hopefully a little
12:40bit excited
12:41about it,
12:41and as you've
12:42heard,
12:43there's certainly
12:43some concerns
12:44that people
12:45are discussing.
12:46I think right
12:46now we're
12:47in a time
12:47where we have
12:47a pretty healthy
12:49balance
12:49of tension
12:51in these two
12:52things,
12:52innovation
12:53and responsibility.
12:55I think that
12:55is what's
12:55propelling us
12:56forward in
12:57the new AI
12:57era.
12:58So we started
12:59this journey
12:59a little bit
13:00earlier than
13:02the rest of
13:03the world,
13:03if we call
13:03our AI
13:04journey,
13:04our current
13:05one,
13:05the explosion
13:06of chat
13:06GPT
13:07in November
13:08of 2022.
13:09At GitHub,
13:10we put on
13:11our GitHub
13:13co-pilot
13:13on the market
13:14in tech preview
13:15in 2021,
13:17end of June,
13:191st of July
13:19of 2021.
13:20So we had
13:20a whole 15
13:21months,
13:22which in
13:22tech time
13:23is quite a
13:24long time
13:25actually,
13:25before we
13:26all woke
13:27up that
13:28November day
13:28and heard,
13:29oh my gosh,
13:30what is this
13:30chat GPT thing
13:31that's going
13:31to change
13:32the world?
13:33But we knew
13:34responsibility
13:35was going
13:35to be key
13:36back when
13:36we were
13:37developing
13:37GitHub
13:38co-pilot.
13:39So we
13:40are very
13:42fortunate,
13:42not only at
13:43GitHub,
13:43do have
13:43a lot
13:44of experts
13:45in this
13:45area,
13:46but we
13:46are a wholly
13:48owned
13:48subsidiary
13:48of Microsoft.
13:50And so we
13:50get to use
13:51Microsoft's
13:52responsible AI
13:53experts in
13:54this area,
13:55which are
13:55world-leading
13:56researchers,
13:58technologists,
13:59policy thinkers.
14:00And so
14:01similar,
14:01I won't repeat
14:01what Barbara
14:02said,
14:02but we have
14:03a process
14:04on how we
14:05develop
14:06responsible AI
14:06and GitHub
14:07works through
14:08those processes
14:08and worked
14:09through those
14:09processes
14:09before we
14:11developed
14:11and put
14:12our product
14:13into the
14:14market.
14:14The great
14:15thing about
14:16this,
14:16I'll just
14:16put a little
14:16plug-in for
14:17open source
14:18and where
14:18we are
14:19as a
14:19society
14:20on
14:20responsible
14:21AI.
14:22It is
14:22taking the
14:23approach
14:23of open
14:24source.
14:25Companies
14:25put out
14:26their
14:26responsible
14:27AI
14:27processes,
14:28their
14:28standards,
14:29so that
14:29others can
14:30learn from
14:30it in the
14:31community.
14:31I think
14:31this is a
14:31really
14:32important
14:32point.
14:33But beyond
14:34the
14:34responsible
14:35AI
14:35development
14:36of it,
14:36we also
14:37learned
14:37very quickly
14:38that we
14:39needed to
14:39listen to
14:40our
14:40community
14:40as we
14:42developed
14:42our
14:42product
14:42and as
14:43we
14:43continue
14:43to
14:44improve
14:44it.
14:44Those
14:44hundred
14:45million
14:45people
14:45that
14:46are
14:46out
14:46there
14:46using
14:46GitHub
14:47have
14:47a lot
14:48of
14:48opinions.
14:49A lot
14:50of different
14:50opinions that
14:51we try to
14:51balance,
14:51but we have
14:52been very
14:52focused on
14:53listening to
14:54our
14:54community
14:55to help
14:55us create
14:56a better
14:57product.
14:59and so as
15:00a result I
15:01would say
15:01we're doing
15:02a pretty
15:03good job
15:04of ensuring
15:05that developers
15:05are better
15:06empowered to
15:07do the
15:07work that
15:07they want
15:08to do to
15:08remove some
15:09of the
15:09toil by
15:10using AI
15:11and the
15:12statistic I
15:13love the
15:13most is
15:14that 75%
15:15of developers
15:16report that
15:16they're happier
15:17using AI in
15:18their jobs
15:19because it
15:19helps them
15:20focus on
15:20the creative
15:20pursuits.
15:21Now, this
15:22is also not
15:23the only thing
15:24that's important
15:24about a
15:25product like
15:25this.
15:26It's not
15:27just about
15:28making our
15:28current
15:28developers happy.
15:30Do we love
15:30that?
15:31Absolutely we
15:32do, but what
15:33is amazing
15:33about an
15:34opportunity like
15:35this is how
15:36we can
15:36potentially expand
15:37what it means
15:38to be a
15:39developer,
15:39expand what
15:40it means to
15:41be a creator
15:42in our
15:43digital future
15:44and as you've
15:45already laid
15:45out, the
15:47number of
15:48women that
15:49are involved
15:49in the
15:50development
15:50process today
15:52is abysmal.
15:53We do have
15:54statistics that
15:55are all over
15:55the map, but
15:56let's say
15:56there is no
15:57way that
15:58more than
15:5825% of
15:59developers in
16:00the United
16:00States are
16:01women and
16:02also maybe
16:0210% around
16:03the world.
16:04So we
16:05think that
16:06this is a
16:07key way to
16:07open up the
16:08circle and
16:08that is
16:09because a
16:10tool like
16:11GitHub
16:12Copilot will
16:13make it
16:14possible for
16:15people to
16:16code using
16:18natural
16:19language.
16:20That means
16:21it does not
16:22matter whether
16:22you speak
16:23French or
16:23you speak
16:24Spanish or
16:25you speak
16:25Swahili or
16:27you speak
16:27whatever language
16:28you speak.
16:28Ultimately in
16:29the future,
16:30our ambition
16:32is that you
16:33can code.
16:33You can be
16:34part of the
16:35creator community
16:36that operates
16:38a computer
16:39which is creating
16:40our digital
16:41future and the
16:42opportunities we
16:42have in this
16:44area with
16:45technology like
16:45this are just
16:46absolutely massive,
16:47but we have got
16:48to do this
16:48responsibly and
16:49we know that
16:50and we
16:51understand that
16:52is why it's
16:53so important
16:53because people
16:54will not use
16:55technology they
16:56don't trust and
16:57society will not
16:58be made better if
16:59we don't do this
16:59responsibly.
17:00Right.
17:01So it's huge.
17:02It's not an
17:02evolution.
17:03It's like a
17:03revolution,
17:04right?
17:05Yes, it is.
17:07It's exciting.
17:08It's moving fast.
17:09Yeah, and as you
17:10just mentioned,
17:11it probably will
17:12change the game
17:13because it will
17:14enable many more
17:15women to be part
17:16of the development
17:19community, right?
17:20Women, all kinds
17:22of people who
17:23today are not
17:24represented in the
17:25developer community,
17:26no matter where
17:27they live, no
17:29matter who they
17:30are, they will
17:32all be better
17:33empowered to
17:35participate.
17:36Yeah, because
17:37right now in the
17:38community of GitHub,
17:41how many women,
17:42what kind of
17:43percentage of
17:43women do you
17:44have?
17:44Do you know?
17:45Well, we don't
17:46track who is
17:48female and who
17:48is male, but we
17:49know by looking at
17:50some of certainly
17:51third-party statistics
17:52that I assume that
17:53our representation
17:54would match
17:55the representation we
17:56see in other
17:57leading indicators.
17:58Great, thanks.
18:01The point that
18:03you were raising
18:04is so important
18:05about inclusion
18:07because if we
18:09look at the
18:09good things of
18:10this kind of
18:11tool, they can
18:12accelerate this
18:13famous inclusion
18:15we are looking
18:16for.
18:16Yeah, it's
18:18really a very
18:19important announcement
18:20you're making
18:21today.
18:21I don't know if
18:22you all realize
18:23what it involves,
18:24what it implies,
18:25but we're going
18:26to watch for
18:26the results now
18:28and see what
18:29the impact.
18:29our CEO was on
18:30stage, did a TED
18:33talk a couple
18:34of weeks ago
18:34that was dropped
18:35yesterday about
18:36our ambition to
18:36dramatically,
18:38dramatically,
18:40dramatically,
18:40what's my,
18:41dramatically,
18:43really increase the
18:45number of developers
18:45around the world.
18:46Dramatically
18:47and drastically.
18:48Dramatically,
18:48drastically,
18:49it's a little AI
18:50help at the moment.
18:51Yeah, because
18:51we're talking,
18:52we're beginning
18:53the talk with
18:54saying there will
18:55be 100 million,
18:56there are 100
18:57million developers
18:58with the GitHub
18:59community and now
19:00you're going to
19:00jump probably to
19:01perhaps.
19:02Let's 10x that.
19:04Billions.
19:05Now, Stephanie,
19:06I turn on to
19:06you.
19:07So, actually,
19:09you're a very
19:09successful business
19:10woman because you
19:11launched KPA,
19:13which was before
19:15you entered a new
19:16business, which
19:17explains why you're
19:18here with us today.
19:19So, you launched
19:21this experience and
19:21then, you know,
19:22you said, okay,
19:23it's not enough,
19:24I want to do more
19:25and then you have
19:26launched a VoliBuy
19:27AI platform that
19:29leverages the power
19:30of generative AI to
19:32manage consumer
19:33contacts for
19:34companies with an
19:36intelligent conversational
19:38agent.
19:39So, it's an
19:40interesting feature.
19:41Can you explain
19:42how you can secure
19:43compliance with and
19:46for your clients,
19:48you know, abiding
19:48bioethical rules?
19:50Yes.
19:50So, hello,
19:51everybody.
19:52I'm Stephanie from
19:53VoliBuy.
19:54And, in fact,
19:55you are right,
19:56ensuring compliance
19:57is very, very
19:58important for
19:59VoliBuy.
20:00So, how we do
20:02it?
20:02First of all,
20:03we have diverse
20:06data sources.
20:08And it's really
20:09important to focus
20:11on mixing all
20:13these data sources
20:15to make sure that
20:16we train our
20:17AI models very
20:20well and also
20:21that we minimize
20:23all the
20:24biases.
20:25You said
20:25biases?
20:26Biases.
20:26Biases.
20:27Thank you.
20:28Thank you.
20:28So, this is really
20:29important.
20:30The sources of
20:31data.
20:32Okay.
20:32Second point,
20:34transparency.
20:36As Barbara
20:37explained to you
20:38concerning Master
20:39Carnan and also
20:40Shelley for
20:41GitHub,
20:42the transparency
20:43is a key value
20:44for us.
20:46And, in fact,
20:47we allow all our
20:48clients and users
20:49to understand
20:51how we built
20:53our algorithms
20:54and how we
20:55use AI.
20:57So, transparency
20:57is key in our
20:59company.
21:00After, we also
21:01organize some
21:02regular audits
21:04with internal
21:06colleagues,
21:07but also external
21:10colleagues,
21:11like, for example,
21:12in France,
21:13INRIA or
21:15EHESS.
21:16Very famous
21:17research centers
21:17and very famous
21:18resources.
21:19Yes.
21:20Thank you.
21:21And, in fact,
21:21they also help us
21:23to identify
21:24all the
21:25base.
21:27Barbara
21:28explained to you
21:29why user
21:30privacy and
21:31security is so
21:33important for
21:34MasterCard,
21:34but I believe
21:36that it's the
21:36same for
21:37every start-ups
21:38and companies
21:39all around the
21:40world.
21:41And, in fact,
21:42here we adhere
21:43to strict data
21:45regulation.
21:46There is no
21:47discussion about
21:48it.
21:48And we ensure
21:50that all the
21:51customer interaction
21:52are secure
21:53and confidential.
21:54And, last point,
21:56for sure,
21:56ethical guidelines
21:58are very
21:59important.
21:59and, in fact,
22:02Volubil,
22:03but also all the
22:04French start-up
22:05and all the
22:05start-up
22:06all around the
22:07world,
22:07are used to
22:09be aligned
22:10with all these
22:11international
22:12standards.
22:13And, for sure,
22:15it's an obligation,
22:16it's a priority
22:17to respect
22:17human rights
22:18and diversity.
22:19and I think
22:21that Barbara
22:22and Shelley
22:22explain this.
22:23The key word
22:24is trust.
22:25If we do all
22:26of this,
22:27trust is here
22:31and if we succeed
22:34to build this trust
22:35with our customer,
22:36business and success
22:38are here.
22:40So, all what I told
22:41you is really,
22:42really important
22:43to build this trust.
22:45So, trust,
22:46in fact,
22:47what you all said
22:47is that trust
22:49requires that
22:50ethical rules
22:51are sort of
22:52respected.
22:54And, we have
22:55a few seconds
22:56left.
22:57Do you, Shelley,
22:58you want to
23:00perhaps develop
23:01a little bit more
23:01about what you do
23:02regarding these
23:04ethical principles
23:05at GitHub?
23:06Sure.
23:08So, you know,
23:09we were,
23:10I mean,
23:11where to start
23:11with ethical principles?
23:12I mean,
23:13you can look online
23:13and see
23:14how much thought
23:16and consideration
23:16has gone into
23:18all of the steps
23:19that we go through
23:20to ensure
23:21that we're adequately
23:21testing,
23:23we are being transparent.
23:24We have a whole
23:25trust center
23:25up on GitHub
23:26that's meant
23:26to walk our
23:28customers through
23:30what we do
23:31in terms of privacy,
23:31what we do
23:32in terms of security.
23:33But we know,
23:34fundamentally,
23:34if we don't create
23:35technology that people
23:36trust,
23:37they won't use it.
23:38And then,
23:39where are we
23:39as a company?
23:40So, it's in our interest.
23:41It's not only
23:42the right thing to do
23:43to achieve our mission,
23:44it's totally
23:45in our interest
23:45as a company
23:46to do this.
23:47And relying on
23:48those technologists
23:49and those experts
23:50that really are
23:50thoughtful about
23:51these things
23:53is very important.
23:54Thanks a lot,
23:55Shelley,
23:55for this.
23:56And, Barbara,
23:57do you want to add up
23:57something regarding
23:58MasterCard?
23:59Because you're very
24:00committed on this
24:00topic too, right?
24:01I think that I will
24:02write argument
24:04on your topic.
24:05It's not only
24:06be ethical,
24:07be reliable,
24:09it's not only
24:10the right things
24:11to do,
24:12it's the smart
24:12things to do
24:13for the business.
24:14So, we believe
24:16in that.
24:17So, we are
24:18acting in that way.
24:20Great.
24:21Stephanie,
24:22a last word?
24:22Just, we need
24:23all genders
24:25in tech.
24:26So, please,
24:26girls,
24:28start to love
24:29mathematics,
24:30start to join
24:32engineer schools
24:34because we need
24:35you in our
24:36tech companies.
24:37Although,
24:38the announcement
24:39that,
24:39that's great,
24:41the announcement
24:41that GitHub
24:42has just made
24:43right now.
24:44You are totally
24:45correct.
24:46We still need
24:46more girls
24:47in math and science.
24:48I think what we
24:49have potentially
24:49the opportunity
24:50to do is help
24:51leapfrog these
24:52decades,
24:54centuries of
24:54educational inequities
24:56with new ways
24:57to engage people
24:58in the ecosystem.
24:59It doesn't mean
24:59you have to study
25:00computer science
25:01from the time
25:01you're five years old.
25:03So, I think it's
25:04a really great
25:05opportunity we have
25:06to try to make up
25:07lost time.
25:08Right.
25:09So, in fact,
25:09what we're doing
25:10together all here
25:11is basically,
25:12you know,
25:13making it possible
25:14for more women
25:14to get involved
25:15in tech and thanks
25:16to all of your
25:17efforts.
25:17Thanks.
25:18Thank you very much.
25:19Thank you.
25:19Thank you.
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