AI: Voice or Victim?

When a group of powerhouse women at the MIT AI-Powered Women Conference asked ChatGPT one simple question, “What do you think I look like?”  the results were… revealing. And not in a good way.

In this live episode from Boston, we sit down with Siri Swahari, Vice President & Partner at CGI, to unpack what happened that night, why AI keeps defaulting to the same stale stereotypes, and how leaders can push for systems that are actually fair, representative, and useful.

Siri breaks down:

The viral moment when AI generated bald white dudes for women of color

Why the problem isn’t “men vs women”… it’s the data

What organizations must fix before unleashing AI tools on their teams

How bias sneaks into models — even when intentions are good

Why representation, guardrails, and real stress-testing matter

What leaders should ask before adopting any AI solution

Why she’s cautious about AI’s pace — but still optimistic

And her work building The Women Executive Circle, a growing cross-state community supporting senior women leaders

If you work in HR, ops, tech, policy, or anywhere AI touches people — this episode will hit home.

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👉 Watch the full episode on YouTube: https://youtu.be/4D78uhi-rw0

What is AI: Voice or Victim??

A podcast that explores how AI is transforming careers, businesses, and industries. Hosts Greg Boone and Erica Rooney deliver real-world use cases and actionable AI strategies to help professionals stay ahead of the curve.

Learn more about your hosts:
Erica Rooney, author of The AI Gap: Women, AI, and the Next Great Leap Forward
Greg Boone, author of AI at the Speed of Trust (available for pre-order)

Siri Swahari: If we see
a problem, it's good.

Make some noise, talk about the problem,
but also think about the solution.

You know, if you had the capacity.

To solve it, how would you solve it?

So that was, that analysis was what I
was thinking that we couldn't include,

you know, uh, making sure there is
representation, there is quality gates

that you, that ensure, like I said, I
think we discussed earlier in the podcast,

like making sure, you know, we, you put
some guardrails in place, testing if

those guardrails are really working,
you know, try to break it and make it.

Greg Boone: AI isn't the future,
it's now, and whether you're in hr,

sales, operations, or leadership, the
choices you make today will determine

whether you thrive or get left behind.

Erica Rooney: Welcome to the AI
Voicer Victim Podcast, y'all.

We are live at the AI Powered
Women Conference at MIT.

And guess what?

We have none other than our girl
Siri, the original OG Siri Soha.

I am so excited to have her.

We are talking all about bias in ai and
y'all, does she have a story for you?

Siri, welcome to the show.

Thank you, Erica.

Oh my gosh.

Do us a favor.

Tell us a little bit about
your background yourself, and

how you're so involved in ai.

Sure.

Siri Swahari: Thank you for
asking for and inviting me to

be part of this whole podcast.

I am honored to be here.

Two of my favorite folks.

Um, and thanks for.

For the great intro.

I don't have to talk about being
the original with all that.

And for those who are listening, if
you don't want your phones to ring,

you know, continue calling me OG Siri.

Um, I never use my full name.

That's what my mom uses
when I'm in trouble.

So for my day job, I'm the vice
president or the sector leader for PMSO.

In industry terms, it is.

Infrastructure and operations, so
anything infrastructure, data centers,

networking, storage, operations like
help desk, service desk, incident

management, operations control.

My team is responsible for providing
support for all of the U-S-C-S-C.

We call the, we call my team the
global technology operations, and

we are a horizontal that supports
all, all 50 states in the United

States, and that is my day job.

Like many women out there,
I have several hats.

I'm also the founder of
Women Executive Circle.

It's a peer, uh, peer community
built for senior women leaders.

And the best part is it's
built by women for women.

So in addition, uh, I am also on
few boards and director, capacity

advisor or a trustee capacity, and
most importantly, my other roles.

Being a daughter, wife, mom of two kids.

And I also, um.

Very, very happy and proud that
I have a wonderful friend circle.

So all of this make makeup Siri.

It's just not me alone.

Erica Rooney: I love it.

That is the full picture of Siri.

Now we were gonna have a totally
different discussion today, full

transparency, but then something
happened last night, late at night,

y'all at dinner after a few drinks.

These women got a little rowdy and
Siri, tell me what happened next.

Siri Swahari: You know what they say?

You know, one or two drinks really
make, makes the conversation lively.

So last night I hosted few women
for dinner, people who were

attending the AI Con, AI powered
Women conference in Boston.

And during the conversation one
of our, one of the members there.

For fun.

She was sharing a story.

What she is a senior vice president at
a construction company, a total badass,

if that is a word that is approved
on the podcast without any filters.

No filters here.

Uh, and someone I really admire,
she is a mom of five kids.

She's a senior vice president at
a construction company, totally

rocking what her responsibilities,
blazing the path, and she has been

using Chad g PT like many of us.

For work, for personal or whatever
reasons, and I think maybe one or two

drinks later, this could have happened.

I'm guessing she went
and queried Chad GPT.

Hey Chad, GPT you.

Based on the interactions you
and I had thus far, can you

tell me something about myself?

Who, can you generate a picture
of me, of who you envision?

And that was the prompt.

A simple prompt.

And guess what?

The Chad Giti drew up a
balding, middle aged white male.

No offense to white male out there.

I mean it is what the Chad g assume and
you know, that caught the party rolling.

And you know, to be fair, we had our fair
share of cocktails and, you know, wine.

Uh, so you know, all of us.

Thought it's fun to see what chat
GPT would generate for each of us.

And boy, oh boy, the chat
last night, it went crazy.

You know, it's just not
the people at the dinner.

It's not just the 15 of us.

There were 50 of us in a, in a WhatsApp
chat, so everyone who was generating

an image of themselves was posting in
the chat, inspiring others to do that.

And it was crazy.

The, there was a, um.

40-year-old, I'm guessing 40 or 30, or let

Erica Rooney: me say middle aged.

No one here is over 26 girl.

Okay.

At least the women, I can't speak
for him, but I, I like that.

Siri Swahari: I, I'll,
I'll take the truth.

A 27-year-old, that's right.

Black woman asked the same question.

It generated a white male person.

I don't know why.

Chad, GPT assumes a white male
who is smart, needs to be bought.

He did generate it.

Similar

Erica Rooney: image.

This is, this is the notice white men out
there that unless you are bald, you're

not considered the it thing by Chad, DPT.

Okay.

Siri Swahari: And, and the fun continued.

Uh, I think for me it generated
a woman, uh, maybe because I was

using it a lot for, uh, writing up
or, you know, looking up research

for the women executive circle.

It got the gender right.

There were a couple of good.

Good correlations.

But then the, the kicker last
night was there was another

woman who asked the same prompt.

It is a simple prompt, generate a
picture of me, of what you think about

me based on her interactions thus far.

And it generated a woman in a executive
suit with the picture, uh, uh, of a slogan

in the back and on the left side, there is
a picture of a couple of cats in frames.

And, you know, to be honest, she was
like, you know what, cha g PT got it.

Right.

You know, I, I am an executor.

I always speak about women
empowerment and I did post a couple

of cat picks, so it got it right.

But the kicker was, you know, when we
zoomed in on that image, the background,

the quote, which she thought cha GPT got.

Right.

You know, what she thought, what
she thought the image sent was,

women belong in places where
the nations are being made.

But then, then we zoomed
in on the picture.

The way the women is
spelled out is we men.

Yeah.

Politically it might sound, I'm running,

Greg Boone: I'm running the prompt now
'cause I wanna see what it says about me.

Yeah, I, I would love to see,
I'm like, oh, I don't, I'm,

I'm so nervous right now.

Siri Swahari: No, I would love to see
what it comes up with, but, and I, I,

I love this part on immediate trying.

It's, it is really, I mean, so all of
us who, if you are, if you ever played

with Chad GPT or played with images,
uh, even if you have the Dali plugin, we

all know it's not good with spellings.

It, it is, right.

It is.

It does mess up sometimes, so we
need to give some plausibility.

But the subtle cues

Erica Rooney: in that one with the
we men belong, like that's too much.

Siri Swahari: I mean,
that, that is so ironic.

I mean, we, we did not know what,
whether to laugh or, you know, it's,

it was a complete ball game last night.

Yes.

And that's when we decided, okay, Erica,
maybe it's time to talk about this.

Well, and

Erica Rooney: I mean, we talk a lot
about bias and we know it, but I think

when you see it in application, and
especially after you've been using a tool

for so long, and I love the example of
the woman who kicked this off because

she is a woman, but in construction.

So all it did was hone in on construction.

Construction equals man, right?

And so it just makes these
generalizations and you know, that's

why it's so important that we have.

Representations of all kinds.

You know, I know Greg has been working
on his image right now, but before he was

like all the way, like 25 certifications
into Chachi, bt, and all this stuff.

He asked for a deck with, you know,
a Cee o and this that and the other.

And of course he kept getting
those old, pale, stale white males.

The Johns, the Toms,
the wait, all of them.

Greg Boone: Wait, wait, wait.

I use CH GBTA lot.

You got some, I've
setted images of myself.

I've done a lot.

It, it tried to ask me about 20
different clarifying questions.

'cause if I think it felt like I was
tricking it and it was like, well, do you

wanna be in this setting or that setting?

I was like, man, you know me.

Go ahead.

It gave me not one, but.

Two options of a white male

Erica Rooney: to choose from,

Greg Boone: to choose from.

Erica Rooney: Here, go.

Lemme see.

Which one do you wanna

Siri Swahari: be today?

Greg Boone: I'm just trying to understand.

Siri Swahari: One has hair, hair handling.

If you don't have enough hair.

Oh, it gave me the, oh, the hair

Greg Boone: was the option.

You could be the silver.

You, you wanna be with the hair
or not having, come on man.

Look, if you don't think there's bias in
these things, like I use it all the time.

Yeah, yeah, it, I've done
deep research on myself.

I mean at this point now I'm like,
look, I don't think you know me at all.

Erica Rooney: No, you're
about to break up.

You are about to break up.

I'm

Greg Boone: going to Gemini,

Erica Rooney: but Siri, you had a really
great post on LinkedIn and I wanna

harp in on this because we are at the
Women's conference and you know, we're

all big women proponents over here.

But you said very specifically,
this isn't about men versus women.

We're not saying absolutely, you know,
they don't belong in those roles or here,

but we're just saying we need to make sure
that everybody has that seat at the table.

But you also said it's not about
men and women, it's about data.

Tell me about that.

Siri Swahari: Exactly that.

So sometimes, you know, people tend to
get defensive when we talk about bias.

Hey, it's just like the example you
were sharing when we were sitting

down for the podcast, how your friend
felt bad when you shared that comment,

you know, not being supportive.

But see, that is not the point that you,
people are honing in on the wrong point.

What we are saying is we need to make
sure the data that we are uploading.

Is unbiased, but we also are not naive.

We know the world out
there is not really easy.

It is not as easy for a woman leader
to succeed as compared to a man.

And obviously the data is reflecting that.

And all these models have been trained
on publicly available data, which.

Had this bias implicitly built into it.

So I'm not calling out on the
founders or the app developers or

the AI dev AI development companies
that they're doing wrong for women.

I am saying we are not doing enough due
diligence before you release a tool to

the world which is easily accessible.

Charge GPT.

I know chat, GPT became synonymous
with AI tools just because it

came first Akin to Google is how,
how Google is used for searching.

But this is applicable to
all the AI tools out there.

How are you making sure the
data bias is being addressed?

What quality gates are you plugging in?

What are the, um, what are
the ethical guidelines?

You know, guard rails.

How are we ensuring that, you
know, what you've implemented as a

guardrail is really actually working?

And this also ties in, you know, I, I
hear your despair, Greg, when you're

saying, Hey, I, I used charge GPT for so
long, but it does not, uh, remember me.

And that you would break up.

It was, it's really funny.

But you know, this also
highlights the main fact.

I think all of you heard about the
MIT paper that got published and it,

all, the hype it cost, I mean, see.

That is what the paper is stating.

I think people were zeroing in on
the wrong thing about, you know,

95% of pilots stating that Yeah,
they're just talking about the

Greg Boone: headline versus
reading the actual that

Siri Swahari: is, that is wrong
because even the data, the

sample size is only three 50.

Uh, that does not justify us claiming
something like 95% across the world.

But the paper did get right, several
other points, and one of them.

Is if you are a human.

You and I interacted several times.

You and I interacted several times.

Your brain stores the memories you,
your brain stores, the interactions

your brain stores, how you I
made you feel, and vice versa.

And the next time we meet, that continues.

But when it comes to
ai, it is a simple tool.

Even though the customized GPT
settings says, go and remove,

remember the memory rules.

Having played it for so long, I
can clearly say that retention, you

know, the, that the database of prior
interactions is not really there like it

would be for a human, which is why most
of these, uh, projects, they tend to

fail because we are, we need to work on
the technology that would get us there

for it to be successful, and which is.

Which is what, uh, we are, I'm hoping
we are going to see with the new

hype word this quarter, the agentic
AI and the agentic AI workflows

and how, how the memory retrieval
is going to be so much better.

So I am very optimistic,
but cautiously optimistic.

But at the same time, it is going
to be a wake up call for all of us.

You know, don't trust
that tool blindly until.

We see proof that the tool is, the tools
out there are performing as expected

and this is something that we need to
continue to speak up, continue to point,

continue to, I mean, I, I actually ta
tagged both the companies, this was not

supposed to be a controversial post.

This was supposed to be, how can
we work together, collaborate, you

know, take our advice, take user
feedback, not only the users that

we are, that are testing your tools.

Also the users that are using, you know,
that they're not paying to for testing.

Take that comment, take that feedback.

You know, do ensure the data set is
not represented based on just size.

You know, we need to make sure,
I, I, I know there are some things

that cannot be said in this day
and age, but that does not mean.

We are not going to focus on the best
outcome of what is right for the world.

Greg Boone: Oh my gosh.

But the, uh, I don't know.

Like, I'm glad you're like the second
or third person today has brought

up that, uh, the MIT article and
I always say the same thing too.

That was insane.

People like read the headlines, but don't,

Siri Swahari: so it is not even the fear.

People reading the headline of the
MIT article, it is, what is that?

Uh, fortune, the Brain
Rock or Fortune 500?

No.

What is that newsletter?

That was the one that picked up.

The le, the MIT paper and published
that and they was there Fortune,

fortune News or something like that?

Yeah.

I, I, I can't recollect at the same, uh,
the, at the top of my mind right now.

But they were the ones
who distill that pushed

Greg Boone: it Yeah.

Siri Swahari: Into that headline.

The, if you look at the, actually
got a copy of that MIT paper, the

whole, uh, uh, uh, I, I was able
to download it and go through it.

They did not claim those
percentages or anything.

It is how it was summarized
by this newsletter.

Yeah.

Newspaper and then every other newspaper
and, you know, every other media outlet

picked on that, that, uh, headline

Greg Boone: because it was
trending at that point.

It's trending.

Right.

You know, as people talk about the,
the psychology behind it, it's the

negativity that actually works.

Yeah.

Right.

If you said that, you know, uh, 25% of
the companies actually were able to.

To create these game changing things.

It wouldn't have got the clickbait.

Yeah, right.

Yeah.

But when they said 95%,
that's a big number.

Right?

And you can run with it.

I was always argue like the same
thing would happen in cloud and

other digital transformation.

Someone would take one headline.

I remember 5G, remember, I don't know.

People used to talk about 5G Metaverse,
uh, ar, vr, uh, I dunno where

blockchain, where all those things go.

Like, it's as if they don't big

Siri Swahari: data, man data.

I don't even talk about, we don't
talk about big data series data was

like, you know, that is the hype.

That is what is, we

Greg Boone: don't talk about that anymore.

Siri Swahari: But, but you see the
one thing that, uh, I think everyone

is saying this, it's just not me.

How AI changed the world is, you
know, in the wilden days, no matter

what big data, even internet, when
something like that got introduced to

the world, the change was happening,
but it was happening maybe twice.

Twice doubling or tripling at the most.

If you are seeing a radical difference
in three years, five years like that.

But when it came to ai,
the growth is exponential.

Exponential.

And you would not know you would be
going to bed, sleeping, uh uh, one

night and wake up the next day to a
changed world, which announced that

deep seek in China released, which
uses so much less energy consumption.

And they also had this research
feature, which, you know, at that time,

charge GPT was only releasing That's.

Oh three version two.

The paid, yeah, paid version.

So it kind of blew everyone's mind, oh,
that AI is going to be so productive.

And so, I mean, especially
the reasoning models, right?

Was something new and you know,
the energy, low energy consumption,

I mean, I, anybody would.

The world needs that we, we
have enough warming out there.

We were literally cooking today when we
went out for lunch to grab outside, you

know, no, I couldn't wait to get back into
a, a temperature control, the environment.

But, so, and you know, I was hearing
someone say in the mo um, one of the,

I think maybe in the panel loud and
county in Virginia, as once they approve

a lot of data centers that, you know,
can support AI workloads, you know.

The energy conception hit so high that
it is, that's gonna melt the grid.

Greg Boone: I mean, I think that, and
it's the only technology out there

that's gonna help us solve the problem.

I think it was a former Google,
uh, Cee o was, I don't know if

he was in Congress or whatever.

I keep seeing it going across
LinkedIn now, but he was talking

about the, the how power hungry it is.

Right.

And what he was saying was that
we have to advance much faster.

Right?

Because you're talking about, I think
it was, uh, what do they say, like

at about 5% adoption, OpenAI was
using about as much energy as the

nation of Barbados a year or two ago.

Right.

So always say to folks,
I'm like, what happens?

I posit, like, what happens
when we get to 20% adoption?

So you're gonna create a world of the
have, the have-nots, the people that

can afford to create their own power.

But this, uh, ex Google executive
basically was saying their, the

average, I think, nuclear plant
is, is like, generates like one,

one gigawatt electricity rate.

And that these, uh, folks that are
trying to raise, uh, for these large

language models said they need.

This year, or by 2027, they need
something around six gigawatts.

So six to 10.

So they didn't need six to 10.

Nuclear.

Nuclear.

Nuclear

Erica Rooney: plants.

Greg Boone: Plants.

Wow.

And they said by 2030
they need 67 gigawatts.

So 67 nuclear plants.

Okay, I have question early go
to fusion or other types of,

Erica Rooney: but I'm glad this is where
I wanna go because I have seen so many

women honestly say like, I don't agree
with how it is impacting the energy.

Therefore I'm not, I'm
not going to use it.

I am going to, you know,
hang my hat on, but it may be

Greg Boone: the only thing
that can help us figure out how

to solve the climate crisis.

Erica Rooney: But if it's
only women who are doing that,

Greg Boone: yeah,

Erica Rooney: then it's not the
women in the room and we still

have representation problems.

So it's like hundred percent.

It's how do, I mean, yes we have to
have responsible usage on all of this,

but like, what do you say to those
individuals who do really wanna protect?

And I said the same thing

Greg Boone: that Siri said, if someone
asked me that question, uh, earlier this

year, and I said, I can't give you all
the, the answers, but what I can tell

you is that deep seek just dropped.

And it was about a month after it dropped.

I said, I don't know if
you paid attention to it.

But they said they were able to, they,
I basically, I'm paraphrasing here,

but effectively what they did was
they took the top 15% of experts, uh,

across the internet and trained off
that versus saying, we need to boil the

ocean to train off every single Yeah.

They're like, what is the
point of training off of every

single human on the planet?

Yeah.

Versus training on the top 15 experts.

So they compartmentalize it and they
did it, and then they did, I wouldn't

call it open source, but it was open
research where they say, look, you can

go check our math of how we did this.

Right.

And so they, what what I was saying
is like, and they proven, I think to

quantify it was around 5.6 million is
what they said it cost to train their

model versus others that were trying to,
but that's why the stock market, I know

Siri Swahari: what the cost,
I haven't heard that, but the

Greg Boone: stock market, that's why the
stock market dropped the first two days.

So it dropped on the, so Deep
Sea comes out on the weekend,

the stock market starts to drop.

Quickly and the, and what people
weren't understanding was it was

starting to drop because all of the
infrastructure, what they were proving

is that you didn't need so much power.

You didn't need so much infrastructure.

And so what people don't understand is
that when you talk about open AI and

these other, you know, organizations, the
jobs that get created, what's going on in

Georgia and Virginia with the data centers
and all this, so people are like, oh, no.

If it doesn't require as much, that means
that all of those construction jobs, all

of these like energy jobs, all, if people
didn't understand, like how did the market

react the way that they did, because they,
what they realized, like if they could

really do it for under 6 million when this
guy over here said he needs to raise a

trillion, there's a chasm of opportunity.

Siri Swahari: It, it's no different from
stopping the electrical cars to succeed

so that the gas industry can drive.

Correct.

Right.

It is a very.

Very akin to that.

I mean, if I'm summarizing, simplify.

Yeah,

Erica Rooney: absolutely.

That's the

Greg Boone: reason why we want Greenland.

Like to be clear, people are
like, why do you want Greenland?

Right?

Because you want the energy resource.

All of this is about energy and people
aren't understanding what's happening.

The deal that was signed with,
uh, was the, the UAE uh, a while

back, I said, just as frankly as I
could say it is, there's just not

enough energy in the US grid, right.

To support our aspirations.

Yep.

Right.

That's the point.

We stopped figuring out how to
actually build, like the last time

someone built anything, like from
like an infrastructure in the US

like that it's been like 50 years.

Erica Rooney: And the point being is
that we need more women involved in

that because hundred percent it probably
would've been billed 49 years ago.

But anyways, dig digs.

I don't,

Greg Boone: I don't disagree,

Erica Rooney: but I do.

I do have a question because you had
some really great points about how we can

steer ourselves towards a better future.

Yes.

And I would love to hear your thoughts.

I know you've said we have to.

Audit the databases, make sure
there's no bias in there, but

like, what else can leaders do?

Siri Swahari: So I, I think, you
know, I won't bore your audience.

It is there in the LinkedIn article.

Uh, but what I always say is even
to not just not me, whether it's

my team, my family, or my kids.

If we see a problem, it's good.

Make some noise, talk about the problem,
but also think about the solution.

You know, if you had the capacity
to solve it, how would you solve it?

So that was, that analysis was what
I was thinking that we couldn't

include, you know, uh, making sure
there is representation, there is

quality gates that you, that ensure.

Like I said, I think we discussed
earlier in the podcast, like.

Making sure, you know, if you put some
quadras in place, testing if those quadras

are really working, you know, try to
break it and make it, uh, confident.

You called it a bias break

Erica Rooney: points

Siri Swahari: and I loved that.

Yeah.

I mean, I was just simplifying it to a
simple word, but I'm pretty sure, and

also these days there are so many AI
companies that are popping up, but if you

are trying to engage with them, make sure.

They comply with those standards.

Just don't go for a shiny object.

That seems good, that seems wonderful.

If, if the ethics, the integrity that
the, the bias checks, the responsible

AI is not part of that foundation, you
know, you are again, getting something

that is not going to be a real diamond.

I mean, I mean, uh, me being a woman,
uh, who loves shopping and jewelry, I had

to, you know, be even diamond somewhere.

I, I

Erica Rooney: love a good diamonds girl.

I love a good diamond
somewhere in the conversation.

Okay.

I definitely do not wanna end this
conversation without hearing more

about the Women's Executive Circle.

So please tell me about that because
this is something, you've founded

it, it's launching in several states.

I wanna give you some airtime
'cause I think it's awesome.

Oh,

Siri Swahari: I'm glad you brought it up.

And I think you should also take credit
for, uh, the way this is growing because

women executors circle is not just me,
it is the women executors that who,

who were my friends, who are now became
my family that inspired its growth.

The one, one of the main
reasons that I agreed to scale.

Despite everything that's going on in my
life is because I saw the miracle happen.

I saw the miracle in August where all
of you rallied together, spent three

and a half hours to help address a
problem that a fellow women executive

was facing, and that was the final.

Uh, that was the straw for you?

That was the, the, yeah.

Sealing the deal.

Seal the deal.

That's the better word.

Because, you know, I've been
getting requests to scale it up

for a long time, but you know,
with my job is quite busy and, you

know, I have other responsibilities
so I was like putting it off.

And for those who don't know
what it is, uh, women executive

circles, it started very small.

It is just few executors who are
me, part of the chief ecosystem.

We decided, you know.

Especially in this age of ai,
you know, nothing beats human,

authentic human connection.

Yes.

And that's what we were trying to achieve.

But you know, we were not a
large enough group for chief to

sponsor or host those sessions.

Like I said, if I see a problem, I
don't wait for someone to solve it.

I solved it myself.

You know, I started hosting and it
was supposed to be a small chiefs get

together, which is like-minded leaders.

And we had a regular cadence there
where we used to discuss, you

know, meet for lunch each other.

And then we

Erica Rooney: grew and we grew and we

Siri Swahari: grew and chiefs,
many chiefs became balanced, but we

didn't want to lose the connection.

Like I said, people became family,
then they started getting plus ones,

you know, other women executors in the
area, uh, who are either part of Athena

or other peer networks or chief ready
or you know, who are on the fence,

whether to pay it is, it is a huge fees.

For folks, especially solo
entrepreneurs or for self-paid members.

So you know, people who are on
the fence, but you know, they

do have the necessary leadership
and experience to be part of it.

So I went back to my drawing
board and I went and renamed it

Women Executors of North Carolina.

But then the magic started when
people from other states visit started

visiting us and you know, attended
our meetups, our dinners gathered.

They just love the
community that we built.

Again, it's nothing beyond a
authentic human connection.

That's it.

It is, it is sisterhood in action
and sometimes it takes someone

who walk the same path as you
to understand the pain points.

Uh, I'm pretty sure many, all of us
have wonderful families, you know,

wonderful friend circle, but sometimes.

What you deal at work or what you deal
in, in a toxic situation, you would be

able to either go to your therapist or
you know, the next best option, speak

with someone who walked the same path
and, you know, get a second opinion.

And the way this, this grew, it,
it is now, it's like we have our

own set of board of directors.

Anytime we have something, you know, we,
we don't even have to meet in person.

We all, we all have a group where we
discuss, where we brainstorm, where we.

Provide guidance, the give and
get, you know, uh, opportunity

for growth and so on.

But when, uh, folks from other states
visited and wanted us, wanted to replicate

something like this, I've been putting it
off because, uh, because of my bandwidth.

But August Meetup was the final straw
when I decided, but I saw the difference

every time we meet at these sessions.

We solve a problem or two, or we find
a revenue, uh, or a source of growth at

the most, it is at least a event out.

It is some, I mean, someone put it
like, you know, it's, it's a place

where I can take the mask off.

Yes.

Because no matter how vulnerable you
might feel or how, when the, if they

imposter syndrome kicks in, or it
does not matter what kind of situation

you're dealing with at home or at work.

You need to be that strong face,
you know, put on that mask and, you

know, go and solve the day, solve
a problem, and put out a fire.

Yeah.

But all of us are human beings.

We will need our own downtime.

Yes.

Time where we can be our true selves.

Yes.

And it is also very confidential
and, uh, group, uh, where we ensure

the confidentiality is maintained.

So.

Erica Rooney: What I love about it and
what you said, and what we're experiencing

here is just, it's this sisterhood.

It's this coming together of like-minded
people who are doing things, which

is why it's so important to have all
of these different representation

and voices when it comes to ai.

So, Siri, with this last question,
what is the thing you are most

excited about when it comes to ai?

Right now

Siri Swahari: it's just not excitement.

I'm also scared.

Erica Rooney: Ah, okay.

Fair.

Siri Swahari: I'm excited about
the possibilities, you know.

So yesterday, I, I, I met my
friend's son who's studying at MIT

who, who was speaking about BLM.

He, he was speaking about leveraging AI
for, uh, robotic works, women like us.

We don't have time to do laundry.

It is if the most toughest show.

Also, I don't want to.

And, and he was like, auntie, you
know, Roomba came, you know, I

mean, I was asking, you know, is it
really something that's possible?

And he was like.

And he was, it is possible,
you know, what about Roomba?

And I said, isn't.

It's not, isn't it too complex?

And you know, he was talking about
some research that he was and some,

uh, conferences that he attended where
the possibility not infinite though.

This is not a distant reality,
let just put that way.

But it's one of the more

Greg Boone: like laundry.

It's funny 'cause I listen to the,
um, AI for Humans podcast and they

always have like a robot like, uh,
section of the show every week.

And one of the things they constantly
talk about is how complex it is to

get a robot to actually fold clothes
because of the physics involved.

Because it's because most clothes and
articles are flimsy and they said, so

they call it that kind of laundry test.

And like people literally out there
building robots to see if they

could finally get to a point, it
would be so nimble where they could.

And so if they can, they think, uh,
there's a lot of great ones that are

coming outta China, but what they're,
you know, and they always call it the

Jetsons moment, like the old cartoon.

Siri Swahari: But it is ironic, you
know, you asked a women leader and then

I was giving an example of laundry.

But you know, I want to also summarize it.

You know, I just don't want it to
generalize it as a household show work.

The reason automation and AI was
invented is to make sure we get

rid off the mundane, dumb, uh,
depressing, repetitive, boring,

Erica Rooney: blah.

Siri Swahari: I, I, I, I remember
the, there was, uh, this LinkedIn

author that I follow, so Rashidi,
she, she was using the four Ds.

She heard it from someone else in a
conference, ll dirty, dangerous, and.

Dingy.

I can't recollect the fourth
one, but let's call it dingy.

But

Greg Boone: she has some great posts.

I know what you're talking about, right?

Yeah.

Siri Swahari: Right.

So I mean, that hit the nail on the head.

Yeah, we, if I can do something easily,
I don't really need AI to do it.

The complex does what feels repetitive,
what feels boring, what does not.

Need implicit instructions.

If that can be automated, that would
free up my brain to do the actual task.

To do the

Erica Rooney: things that fill your cup.

Yes.

Oh my gosh, I love that.

Yep.

Siri Swahari: And uh, I just
wanna circle back on the VC topic.

So Women Executive Circle it is, the
acronym is WEC, but we are going, we

phonetically call it as we see, as in we
see each other, we support each other.

We see Yeah.

And uplift each other.

I'm glad to report the pilot.

It was not supposed to be a pilot.

It, the, the idea that group formed
in North Carolina, but that's parked

or set the path ahead for 10 states.

And

Greg Boone: when we going on global,

Siri Swahari: we, the plan is to go, I
mean, I have people from London and uh,

Portugal asking if they can start it.

I said.

Baby steps.

You know I have the corporate hat.

She said, lemme handle the US for opioid,

Greg Boone: North
Carolina just for a week.

And now this corporate hat comes in.

You

Siri Swahari: don't scale too fast.

That's right as it fails.

So it is intentional scaling.

I have 10 states ready and
everything is voluntary.

This is held by CEOs, by
leaders, by doctors who have.

So who are so busy, but they all heard
the call and they, they rose to the

occasion to give their time back, and I'm
glad to report Florida is the first date

that is going to pilot this September.

Greg Boone: Here we go.

Oh, Florida person here.

Oh,

Erica Rooney: Florida girl.

Okay.

He's made

Greg Boone: her year.

Erica Rooney: That's all right.

That's right.

Oh my gosh.

Well, Siri, thank you so much
for joining us here at the AI

Powered Women's Conference at MIT.

You are making changes.

Thank you for all you're
doing with We see.

I'm just so excited to have
you on the show, so thank you.

Thank you.

Thank you for having me.

Thank you.

Thank you.

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