[00:00:05.06]
There was many of you know as
you know we all want to hear.
[00:00:09.06]

[00:00:10.07]
About the great pleasure behind us.
[00:00:13.06]

[00:00:15.10]
Years.
[00:00:15.22]

[00:00:17.14]
Kathy I think you're probably the youngest
distinguished a lot of Relpax time that
[00:00:20.21]

[00:00:20.21]
we've had so congratulations for that.
[00:00:23.01]

[00:00:24.18]
I misunderstood got to.
[00:00:25.18]

[00:00:28.21]
Remember the 1st time at.
[00:00:29.19]

[00:00:31.00]
This where I was the advisor
Pura Bajan Cup project wise but
[00:00:35.20]

[00:00:35.20]
I've never before that because he can talk
to me she was a student at Georgia Tech
[00:00:39.16]

[00:00:39.16]
already and contact and
software plus he'll get laid again let's
[00:00:44.15]

[00:00:44.15]
just take this one here just it's
worth us if we don't offer this.
[00:00:48.21]

[00:00:50.13]
As saying I can make it
happen I don't know how but
[00:00:52.20]

[00:00:52.20]
we talked residential anyway and
I sure guys actually
[00:00:57.03]

[00:00:57.03]
were separated organize a group of French
students to do projects in the class.
[00:01:00.23]

[00:01:02.01]
It was pretty amazing I think that
story to me says a lot about Kathy and
[00:01:05.12]

[00:01:05.12]
her determination to just make things
happen even when we're told possible
[00:01:11.10]

[00:01:11.10]
so since there really honestly
got to see the 2 long list
[00:01:15.09]

[00:01:15.09]
of all sure just a few highlights
She's one of the founders.
[00:01:17.22]

[00:01:21.01]
Of ministration she was a 20000
Media Lab fellow just the point at
[00:01:25.08]

[00:01:25.08]
the Harvard Kennedy School were
teachers marriage but in society
[00:01:29.04]

[00:01:30.04]
also with the Berkeley winds that were
hugely helpful technology working group.
[00:01:34.08]

[00:01:35.20]
With me about your Georgia Tech she's a
polar opposite of what we're calling her.
[00:01:40.09]

[00:01:42.04]
Which would.
[00:01:43.14]

[00:01:43.14]
Connect to what you're talking
about today when a time
[00:01:46.12]

[00:01:46.12]
Ok let's welcome you back to what.
[00:01:48.17]

[00:01:53.02]
I feel so good to be back thank you
Farai Freeman having me this is wild.
[00:01:57.11]

[00:01:59.03]
So scared.
[00:02:00.14]

[00:02:02.04]
Of Thanksgiving lunch I really just want
to read if there's a word that sums up
[00:02:06.17]

[00:02:06.17]
my time here going to tack at
a deep sense of gratitude.
[00:02:10.15]

[00:02:10.15]
And I think I'm a tie
that back to the work and
[00:02:14.16]

[00:02:14.16]
response of computing and public interest
technology and what that means but
[00:02:19.04]

[00:02:19.04]
I really have this deep
sense of gratitude for
[00:02:21.12]

[00:02:21.12]
what Georgia Tech gave me one being
an in-state student in Georgia was really
[00:02:27.02]

[00:02:27.02]
how how many before how many folks in
here undergrad computer science students.
[00:02:31.13]

[00:02:33.04]
Co-op that many.
[00:02:33.23]

[00:02:35.00]
How many are graduate students.
[00:02:36.17]

[00:02:39.03]
How many are c.s. students.
[00:02:40.17]

[00:02:42.08]
Please So other h.c.i. free to.
[00:02:45.06]

[00:02:47.16]
Call and that's helpful but
also my miss how many of you
[00:02:52.13]

[00:02:52.13]
have worked in a big tech company however
you would define big tech company.
[00:02:55.23]

[00:02:59.08]
How many you have worked in government.
[00:03:00.15]

[00:03:04.15]
You know if.
[00:03:05.11]

[00:03:07.00]
You mean does University
count as government
[00:03:09.07]

[00:03:10.09]
as a joke because of the bureaucracy or
as because it is interesting
[00:03:14.18]

[00:03:14.18]
because resi institution how many
of you have worked in a federal or
[00:03:17.07]

[00:03:17.07]
state governments but
is not an academic institution.
[00:03:20.08]

[00:03:22.02]
Where did you all work.
[00:03:23.02]

[00:03:28.11]
Which branch.
[00:03:29.02]

[00:03:30.09]
Thank you for your service.
[00:03:31.08]

[00:03:32.10]
My brother was r.t.c.
[00:03:33.18]

[00:03:33.18]
here at a tech and he's an active
military Marine where else that you are.
[00:03:37.15]

[00:03:39.19]
Actually since I have you answering
questions what do you think about tech and
[00:03:44.12]

[00:03:44.12]
ethics I'll give you folks a few moments
of think about this they got to economics.
[00:03:49.13]

[00:03:51.02]
What pops in your mind at the top of the
thing that pops into your mind about what
[00:03:54.12]

[00:03:54.12]
that even means.
[00:03:55.08]

[00:03:58.04]
And I would love for
a few people to just say that out loud.
[00:04:00.13]

[00:04:02.04]
Yes.
[00:04:02.16]

[00:04:03.23]
Data privacy.
[00:04:04.21]

[00:04:06.12]
She killed her veil of capitalism just for
the what we needed.
[00:04:11.23]

[00:04:14.06]
Of their.
[00:04:14.18]

[00:04:16.03]
Data collection.
[00:04:17.07]

[00:04:18.18]
Privacy data collection surveillance.
[00:04:20.23]

[00:04:24.02]
Equity thank you for
that a committee justice.
[00:04:28.13]

[00:04:30.07]
Fairness and.
[00:04:30.20]

[00:04:35.17]
Combating disparities.
[00:04:37.05]

[00:04:38.13]
Were of public interest
what does that mean.
[00:04:40.15]

[00:04:44.12]
There's no uniform definition for
any of us so
[00:04:47.18]

[00:04:47.18]
anything you say is probably something
that someone has also fought for he said
[00:04:52.03]

[00:04:52.03]
What do you think of when you think of
public interest or public interest talk.
[00:04:55.02]

[00:04:56.10]
A mystery at the side until
someone raises their hands.
[00:04:58.20]

[00:05:00.23]
For service service to.
[00:05:04.10]

[00:05:06.12]
Service to the public.
[00:05:07.12]

[00:05:10.04]
And.
[00:05:11.15]

[00:05:11.15]
Utilities let's agree there's actually
a lot of conversation around utilities and
[00:05:16.04]

[00:05:16.04]
technology and equity and justice as well.
[00:05:18.16]

[00:05:20.10]
And you want all over here Ok.
[00:05:23.00]

[00:05:28.07]
So.
[00:05:28.19]

[00:05:29.20]
I have a lot of gratitude for this place
because not only did it leave me with
[00:05:35.00]

[00:05:35.00]
this amazing computer science degree
the on its own and the c.s. part of it.
[00:05:40.22]

[00:05:40.22]
Is internationally recognized and deemed
as one of the best programs in the world.
[00:05:44.21]

[00:05:46.01]
But then while I was here.
[00:05:48.01]

[00:05:49.06]
You pretty much as
an undergrad stumbled into
[00:05:54.23]

[00:05:54.23]
research as a as a freshman undergrad
I was in this building and met.
[00:05:59.04]

[00:06:01.01]
Lena Brashear who let me do research
with her as a 17 year old undergrad.
[00:06:07.06]

[00:06:08.10]
And how much that opened the door to so
many other things there are countless
[00:06:12.21]

[00:06:12.21]
study abroad programs there were if you
wanted to work across departments and
[00:06:18.01]

[00:06:18.01]
figure out like biomedical
engineering computer science or
[00:06:21.14]

[00:06:21.14]
anything else there were just
people here that made it
[00:06:24.17]

[00:06:24.17]
possible to do any of
that any of that work.
[00:06:27.10]

[00:06:28.23]
And although I was talking to few folks
I was a I don't know if it was is like
[00:06:32.13]

[00:06:32.13]
the public nature of Georgia Tech of where
I always felt like there was a sense
[00:06:37.11]

[00:06:37.11]
of community and and working with the
community while you're a student here and
[00:06:42.02]

[00:06:42.02]
it took I think going away and
[00:06:43.18]

[00:06:43.18]
seeing what other institutions were
like especially some of the private
[00:06:47.02]

[00:06:47.02]
institutions to really recognize how
special it was to be at Georgia Tech.
[00:06:50.09]

[00:06:51.10]
And and
not only study computer science but
[00:06:54.19]

[00:06:54.19]
have all these other fingers in all
these other fields and areas and
[00:07:00.02]

[00:07:00.02]
have like this deep sense of community
with it and then I think what was also
[00:07:04.00]

[00:07:04.00]
normal to me at Georgia Tech and
I didn't realize this when I was here
[00:07:09.01]

[00:07:09.01]
was the fact was you know I thought part
of me doing deep research were best.
[00:07:13.08]

[00:07:14.21]
And Amy I think best at one point you or
I ran into you at some like i.b.m.
[00:07:19.14]

[00:07:19.14]
thing in the Bay Area and
I think you were pregnant.
[00:07:23.02]

[00:07:24.14]
But that mattered because
I was surrounded by these.
[00:07:30.04]

[00:07:30.04]
Brilliant professors.
[00:07:31.10]

[00:07:32.11]
Who had kids who had found leaves and
are also doing great research
[00:07:35.15]

[00:07:35.15]
who are advising companies and doing all
these things and that was my normal.
[00:07:38.15]

[00:07:39.20]
And again I think that's going to
tie back to some of this work and
[00:07:42.23]

[00:07:42.23]
what that really really means because
going into the tech industry and
[00:07:45.23]

[00:07:45.23]
going to work at a place like Google and
realizing what I experience at your attack
[00:07:50.02]

[00:07:50.02]
was the number of women who are and
faculty positions who also.
[00:07:53.23]

[00:07:56.06]
Were themselves at work I my my
1st year here I met Monica sweat.
[00:08:01.19]

[00:08:03.02]
People like bar barracks and
have lunch with me.
[00:08:05.11]

[00:08:06.12]
And I was just.
[00:08:07.23]

[00:08:09.06]
Like Jillian Hayes who's
now the dean over at u.c.i.
[00:08:11.23]

[00:08:11.23]
Marine Biggers may want all these people
who taught me Computer Science plus.
[00:08:16.21]

[00:08:18.12]
Bring your whole self to work plus
thinking about society and communities and
[00:08:22.10]

[00:08:22.10]
different kinds of ways and
not a lot of computer science programs
[00:08:27.07]

[00:08:28.07]
do that both in practice of what
the cricket looks like but also
[00:08:31.23]

[00:08:31.23]
what the faculty members are interested
in and I think I bring this up here at
[00:08:35.12]

[00:08:35.12]
Georgia Tech as I have a deep sense of
gratitude for bringing that to me but
[00:08:38.13]

[00:08:38.13]
also I think Georgia Tech is in a very
unique position to really really lead
[00:08:42.20]

[00:08:42.20]
in this time of public interest and
tech and ethics because there's so
[00:08:46.03]

[00:08:46.03]
much foundational work that's been done
here with both the a.c.i. program and
[00:08:50.06]

[00:08:50.06]
the g.b.s. center and
even just other parts of the computing
[00:08:55.18]

[00:08:55.18]
degree program even if it's not
everyone that has been either
[00:09:00.14]

[00:09:00.14]
community focused or been leading in
ways that I think other places are.
[00:09:05.17]

[00:09:06.22]
Aren't there yet so they give for
being those examples for me and for
[00:09:10.22]

[00:09:10.22]
allowing me to do the kind of research so.
[00:09:13.11]

[00:09:14.17]
What I'll give you a little background
of what brought me into this work and
[00:09:18.04]

[00:09:18.04]
then I hope today will be spread to parts
[00:09:21.19]

[00:09:21.19]
kind of what brought me into this work in
the landscape of the space of Ethics and
[00:09:25.22]

[00:09:25.22]
Public Interest tack and
then what I see as the next.
[00:09:30.02]

[00:09:30.02]
Things are on the horizon and areas where
I think many of you either faculty or
[00:09:34.14]

[00:09:34.14]
students can really have
a big play in this.
[00:09:37.10]

[00:09:39.21]
So I was an undergrad c.s.
then went on to Georgia Tech.
[00:09:42.06]

[00:09:43.17]
And I have a few but
see earlier said something like
[00:09:49.02]

[00:09:49.02]
it seems like you've had kind of
an interesting career that went around and
[00:09:54.12]

[00:09:54.12]
so I guess though what I was afforded this
opportunity to jump are all these things
[00:09:58.09]

[00:09:58.09]
because of the degree that you talk
to me which is awesome so yesterday.
[00:10:01.09]

[00:10:02.21]
I started out as Actually I was a co-op.
[00:10:05.18]

[00:10:06.23]
At the Georgia Tech Research Institute
working on flight simulation software for
[00:10:11.03]

[00:10:11.03]
the department defense and realize I
didn't enjoy that environment that much
[00:10:16.10]

[00:10:16.10]
but it taught me a lot about what it was
like to be a government subcontractor of
[00:10:20.14]

[00:10:20.14]
sorts of just took that away in
the back of my head for a little while.
[00:10:23.08]

[00:10:24.17]
And then I think the most typical
route of going to Google and
[00:10:28.12]

[00:10:28.12]
being a product manager at Google for
for a while.
[00:10:32.18]

[00:10:33.23]
And then going on to grad school and
I think another
[00:10:36.15]

[00:10:36.15]
pivotal point was there is this how
many of you have heard of the magic cup.
[00:10:40.03]

[00:10:42.02]
Cause the magic cup is
a play on the World Cup but
[00:10:47.07]

[00:10:47.07]
for nerds so instead of going around
the world and having soccer competitions
[00:10:52.10]

[00:10:52.10]
you have Microsoft runs and you have these
tech competitions with people around
[00:10:56.23]

[00:10:56.23]
the world and there's a local competition
in the state in your country and
[00:11:01.11]

[00:11:01.11]
then you represent your country
on the international level so
[00:11:04.10]

[00:11:04.10]
I was in grad school and
Mark Rey and I just.
[00:11:06.11]

[00:11:07.12]
A one day with a computer lab and
we're like let's enter the competition and
[00:11:11.17]

[00:11:11.17]
we've built back in 2007 or 8 I don't
remember the year a sentiment analysis
[00:11:16.22]

[00:11:16.22]
system for our online communities which
at that time seemed interesting and
[00:11:22.17]

[00:11:22.17]
novel and now we know there's a lot of
implication around sentiment analysis and
[00:11:26.14]

[00:11:26.14]
I algorithms on online communities
on Twitter was just starting out and
[00:11:31.20]

[00:11:31.20]
we ended up winning 1st place
representing the u.s. and Keith and
[00:11:35.21]

[00:11:35.21]
up one of our just took time out of his
day to be one of our advisors far for
[00:11:41.06]

[00:11:41.06]
that magic but that was one.
[00:11:43.03]

[00:11:44.08]
At that time that was like a close if
I got to anything that seemed like
[00:11:47.17]

[00:11:47.17]
a computing for good public interest
thing and I remember computing the term
[00:11:54.01]

[00:11:54.01]
computing for good was starting to become
a thing I don't know this is true but
[00:11:57.22]

[00:11:57.22]
I think that was even controversial
around the term computing for
[00:12:01.01]

[00:12:01.01]
a good consumer like why do you think
you're doing computing for good I'm.
[00:12:06.19]

[00:12:06.19]
I'm doing computing for get to because
I'm going to change the world and
[00:12:10.10]

[00:12:10.10]
I'm going to connect people and I'm going
to spread information to people who don't
[00:12:13.22]

[00:12:13.22]
have it and that's I think that moment
also stuck with me this idea that
[00:12:18.21]

[00:12:18.21]
yes we can have a computing for a group
group which is really important but
[00:12:23.14]

[00:12:23.14]
also what do we do when the whole body of
Engineers also believe that everyone is
[00:12:28.04]

[00:12:28.04]
doing good and I get put a plan to
the opinion that somewhere but good to
[00:12:33.23]

[00:12:33.23]
know that there's a backlash against using
this term and what that really means.
[00:12:37.10]

[00:12:38.15]
So that imagine how about exposure
to a bunch of people who.
[00:12:41.19]

[00:12:43.15]
Enter this competition because they want
to build software to do everything from
[00:12:47.00]

[00:12:47.00]
having a vending machine that reads
your temperature so a doctor remote
[00:12:51.21]

[00:12:51.21]
area can can assess you and that was
a Brazilian team that got 2nd place.
[00:12:55.18]

[00:12:56.21]
And it was a it was also exposed to all
these teams from around the world who
[00:13:01.20]

[00:13:01.20]
were able to think about solving tech
problems in a deeply localized kind of way
[00:13:06.02]

[00:13:06.02]
which also was a loss on hey.
[00:13:07.23]

[00:13:09.05]
All of us sitting in the Silicon Valley
can't think of all the world's problems
[00:13:13.12]

[00:13:13.12]
and just build things and assume that we
can solve problems in India and Brazil and
[00:13:17.17]

[00:13:17.17]
me and Mar and Vietnam and
China and all these other places
[00:13:21.10]

[00:13:21.10]
just because their solutions are so so
different and that also stuck with me and
[00:13:26.03]

[00:13:26.03]
now at a time when we now see these big
tech companies having really really
[00:13:30.13]

[00:13:30.13]
difficult ethical problems when they
have done a really poor job localizing.
[00:13:36.04]

[00:13:36.04]
For example if Facebook were 2 or
more to enter the market like me m.r.
[00:13:40.18]

[00:13:40.18]
were out deeply understand the political
climate of a place like me and
[00:13:44.06]

[00:13:44.06]
Mar understanding the rapid growth of
technology understanding how information
[00:13:48.23]

[00:13:48.23]
spread understanding deep rooted racism
and knowing how the spread of information
[00:13:53.03]

[00:13:53.03]
there in a vacuum of
information can cause certain.
[00:13:56.06]

[00:13:57.22]
Human rights problems and so
that experience was a lot of exposure
[00:14:02.22]

[00:14:02.22]
to Texas from around the world thinking of
ways to solve problems localized I saw God
[00:14:08.00]

[00:14:08.00]
put a pin in that part 2 of the tortoise
deeply understanding local regions
[00:14:14.11]

[00:14:14.11]
as we build technology but also
recognizing how most of my colleagues and
[00:14:19.15]

[00:14:19.15]
peers and in our training we just
don't learn about that very often.
[00:14:22.20]

[00:14:24.02]
So that was a magic cup
then went to Google and
[00:14:26.10]

[00:14:26.10]
pretty much had back in
less think 20078 The most
[00:14:31.05]

[00:14:31.05]
typical experience which was you land at
Google everyone tells you you're changing
[00:14:34.21]

[00:14:34.21]
the world you're Do you know evolve
which was still the logo at the time and
[00:14:39.20]

[00:14:39.20]
every single t.g. I asked which was every
single town hall we had was someone
[00:14:43.23]

[00:14:43.23]
like a product manager who's on a stage
just like jumping with excitement telling
[00:14:48.02]

[00:14:48.02]
the whole company about something like you
know we have this new feature it can be on
[00:14:51.22]

[00:14:51.22]
your phone you can walk into a building at
any point in time it can tell you exactly
[00:14:56.19]

[00:14:56.19]
how long it'll take you to get home
without even knowing because you step into
[00:15:00.12]

[00:15:00.12]
the building at 5 o'clock and it knows
you have to pick up your kids at 530 and
[00:15:03.14]

[00:15:03.14]
I'll give you a notification and you'll
do all these things and so seamless and
[00:15:07.05]

[00:15:07.05]
it's so awesome We're going to change
the world and that was pretty much
[00:15:10.14]

[00:15:10.14]
every single town hall meeting and
it stopped there there was never a.
[00:15:15.19]

[00:15:15.19]
But what does that really mean for
someone's privacy or.
[00:15:18.22]

[00:15:20.12]
But what if someone used it in this way
and what if you don't really want people
[00:15:24.08]

[00:15:24.08]
knowing where you are and there was
never that kind of a conversation and
[00:15:28.13]

[00:15:28.13]
I also never saw any issue with
that because no one talks about it
[00:15:32.13]

[00:15:32.13]
at these companies I don't know those for
those of you who work at big companies or
[00:15:36.17]

[00:15:36.17]
know this jives of how you've experience.
[00:15:38.15]

[00:15:39.18]
Being there but up until probably 3 or
4 years ago it was still very much a look
[00:15:44.18]

[00:15:44.18]
at all the ways we're going to change the
world because we have these skill sets and
[00:15:48.23]

[00:15:48.23]
it's going to be awesome and
tech is great.
[00:15:51.10]

[00:15:53.11]
And not necessarily think about some
of the negative side effects and
[00:15:58.03]

[00:15:58.03]
I think I actually think that's where
there definitely have been researchers at
[00:16:01.17]

[00:16:01.17]
Georgia Tech who've been thinking about
that for a long time even if it's not
[00:16:05.14]

[00:16:05.14]
exactly phrased as ethics or
responsibility or anything like that.
[00:16:11.10]

[00:16:12.18]
So that was the experience at Google for
a period of time so the Google break.
[00:16:17.23]

[00:16:19.18]
Went to i.b.m. and this is another beast
so I when I think of the ethics and
[00:16:24.13]

[00:16:24.13]
responsibility conversation we have the.
[00:16:26.15]

[00:16:27.18]
The bios and the fairness and the examples
of echo chambers on Facebook and
[00:16:33.06]

[00:16:33.06]
Google labeling humans as gorilla
was we have discrimination and
[00:16:38.14]

[00:16:38.14]
Sharon's policies etc and then we now
also have another world of at these
[00:16:44.07]

[00:16:44.07]
conversations where we've now seen many
employees at big tech companies I mean if
[00:16:48.12]

[00:16:48.12]
you're familiar with the walkout that big
tech companies it's pretty widely covered.
[00:16:52.07]

[00:16:53.14]
Whereas the other side of that is.
[00:16:56.17]

[00:16:56.17]
Let's say we've got all the technology
the best ability we have a piece of
[00:17:00.07]

[00:17:00.07]
tech because the issue with the Google and
Facebook scenario is you're like
[00:17:05.03]

[00:17:05.03]
Ok engineers aren't really trained to
really think about some of these problems
[00:17:09.14]

[00:17:09.14]
when we're building technologies for
different countries we don't think about
[00:17:12.05]

[00:17:12.05]
localization when we have certain data
sets that not comprehensive enough
[00:17:17.07]

[00:17:17.07]
therefore we have bias etc etc But
then we also have another wall with i.b.m.
[00:17:22.19]

[00:17:22.19]
type where how many of you are familiar
with i.b.m. in the Holocaust.
[00:17:26.06]

[00:17:27.11]
Is that there's a book called i.b.m.
[00:17:28.18]

[00:17:28.18]
in the Holocaust the gist of it is that
i.b.m. as a contractor or a company.
[00:17:33.09]

[00:17:34.23]
Do what they do best which is they sell
to organizations including governments
[00:17:39.23]

[00:17:39.23]
around the world and their technology
was used during the Holocaust and
[00:17:44.23]

[00:17:44.23]
the ethical question there for people is
if you're an engineer on that team of
[00:17:49.13]

[00:17:49.13]
your work in that company how
is your technology being used so
[00:17:53.08]

[00:17:53.08]
which is a different kind of an ethical
conversation right it's less of the what
[00:17:58.03]

[00:17:58.03]
are you building and it's more is now
you've got a thing and it has dual uses
[00:18:02.00]

[00:18:02.00]
and has lots of different kinds of uses So
the cases we've seen what walkouts
[00:18:05.23]

[00:18:05.23]
is we have Google and project maven so
Google in the department defense we have.
[00:18:10.13]

[00:18:11.17]
Sales Force and
I we have these other cases and
[00:18:16.12]

[00:18:16.12]
I think the thing to and that's what I
thought about what got the experience at
[00:18:20.16]

[00:18:20.16]
i.b.m. as a contractor for
the government thinking about.
[00:18:25.09]

[00:18:25.09]
Where and how we should deploy technology
but also understand the complexities
[00:18:31.05]

[00:18:31.05]
of it because on one hand you have people
that say don't work with any government
[00:18:35.11]

[00:18:35.11]
on the other hand I'll get to this as
well I work in the federal government for
[00:18:38.06]

[00:18:38.06]
years and if you're thinking about public
interest tech do you want to world or
[00:18:42.13]

[00:18:42.13]
not over there is no technology
in our government and so
[00:18:46.01]

[00:18:46.01]
there's also another argument for we need
some of the best technologists working on
[00:18:51.10]

[00:18:51.10]
our military programs our education
programs our veterans programs as well and
[00:18:56.20]

[00:18:56.20]
it's a complicated issue that I don't
think anyone has it right I know tech is
[00:19:01.19]

[00:19:01.19]
doing some work with public policy and
computing.
[00:19:06.16]

[00:19:07.21]
And has done work for some time now in
this space but no one has it's easy
[00:19:12.05]

[00:19:12.05]
to reduce that down to don't work for
government or work for government or
[00:19:15.14]

[00:19:15.14]
something but it's a really complex
issue of how do we use technology to
[00:19:21.00]

[00:19:21.00]
benefit the public good in the government
sense so if any of you are working for
[00:19:26.04]

[00:19:26.04]
a government contractor It's a fascinating
lesson of all the complexities of
[00:19:30.19]

[00:19:30.19]
why the foundational technology at least
in the United States is completely broken
[00:19:35.20]

[00:19:35.20]
from how we do contracting for technology
to the type of people that get deployed
[00:19:40.15]

[00:19:40.15]
the Miter person probably has
a lot of experience with this of
[00:19:43.23]

[00:19:43.23]
the types of technology and
how it gets deployed inside government and
[00:19:47.12]

[00:19:47.12]
how governments manage programs and
what it's like to be an engineer in
[00:19:51.12]

[00:19:51.12]
the government setting whether at
the city state or federal level.
[00:19:54.13]

[00:19:55.23]
That was i.b.m. came back to Google for
a little bit and just have fun and
[00:20:00.17]

[00:20:00.17]
if you want to learn more
about this setting a year and
[00:20:02.20]

[00:20:02.20]
a half working in the people
operations organization and
[00:20:07.10]

[00:20:07.10]
I highly recommend being a tech
person working in and the h.r.
[00:20:11.12]

[00:20:11.12]
system because you've got to learn
the inner workings of how a company hires.
[00:20:14.23]

[00:20:16.12]
And I want to deeply believe that any
organization whether it's government or
[00:20:20.16]

[00:20:20.16]
private sector the hiring of the people
you take in is probably the most
[00:20:24.02]

[00:20:24.02]
critical part of any.
[00:20:24.22]

[00:20:24.22]
Organization and.
[00:20:26.02]

[00:20:27.11]
Got to see again how excited the team
was about tracking every move
[00:20:32.22]

[00:20:32.22]
of them slowly to be like we can find out
we can do analytics to find out who might
[00:20:37.11]

[00:20:37.11]
leave in a few years and then throw more
stock options at them and we want to list
[00:20:41.06]

[00:20:41.06]
of all the people and their likelihood of
probability of leaving and we want all
[00:20:45.05]

[00:20:45.05]
these all these numbers and just
watching how much in the name of good.
[00:20:48.20]

[00:20:50.16]
A company was hired full teams
of engineers and researchers and
[00:20:54.19]

[00:20:54.19]
data scientists to just
analyze its own people but
[00:20:59.02]

[00:20:59.02]
again never having the additional
conversation of what does that really mean
[00:21:03.23]

[00:21:03.23]
and we're starting to see that now
with people studying spotlights
[00:21:08.18]

[00:21:08.18]
on not just hiring algorithms
hiring practices and
[00:21:12.05]

[00:21:12.05]
how companies treat their employees and
what they track with their employees and
[00:21:15.22]

[00:21:15.22]
we're starting to see more awareness of
that now but that was also another great
[00:21:19.20]

[00:21:19.20]
lesson on being inside an organization
with a lot of excitement around a piece
[00:21:24.23]

[00:21:24.23]
of technology to do something with very
little questioning around it and I think.
[00:21:30.07]

[00:21:31.14]
I think there's definitely this is more
for you all somewhere with the way we
[00:21:36.13]

[00:21:36.13]
train our our computer scientists and
researchers are people
[00:21:42.05]

[00:21:42.05]
who end up going to industry and what you
do when you're in that kind of situation.
[00:21:45.05]

[00:21:46.19]
But that's going and me and
I think industry shifting a bit
[00:21:50.02]

[00:21:50.02]
where employees for the most part
are recognizing this more but
[00:21:54.14]

[00:21:54.14]
I think that's actually a crux of
some of the issues that we're seeing.
[00:21:57.14]

[00:21:58.16]
In the tech industry where there's a lot
to get back to there's a lot of excitement
[00:22:02.06]

[00:22:02.06]
about what technology can do in this go
ahead and do it without necessarily having
[00:22:05.19]

[00:22:05.19]
a conversation about whether or not we
should do it so then the pivot from.
[00:22:10.09]

[00:22:12.17]
Google private sector of
the world back in 2013
[00:22:18.10]

[00:22:18.10]
how many of you have heard of healthcare
dot gov in the United States.
[00:22:22.12]

[00:22:23.15]
You laugh What did you hear about that so
in your and then the summary a few folks
[00:22:28.14]

[00:22:28.14]
with what would your summary of what
happen with health care dot gov 6.
[00:22:31.21]

[00:22:34.06]
6 people and
all of the 1st day true story.
[00:22:37.04]

[00:22:38.10]
Or else you know about
health care dot gov.
[00:22:39.22]

[00:22:43.17]
And you on.
[00:22:44.05]

[00:22:47.20]
How do you think.
[00:22:48.21]

[00:22:49.23]
Initially.
[00:22:50.23]

[00:22:52.18]
Actually me backtrack when you launch
any system how do you think you should
[00:22:57.20]

[00:22:57.20]
what should you what should you put
in place to make sure it works and
[00:23:01.02]

[00:23:01.02]
figure out points of failure
what do you normally do.
[00:23:03.01]

[00:23:04.08]
You test how do you test that
what do you have in place.
[00:23:06.02]

[00:23:12.02]
Usability testing private seeing walk
through and testing at all sometimes just
[00:23:18.18]

[00:23:18.18]
some testing would you put tracking on the
system any kind of so health care not got.
[00:23:26.17]

[00:23:30.02]
There I believe over 60 so a total of
maybe over 60 contractors when you
[00:23:35.00]

[00:23:35.00]
came down to was one make main
contractor and a bunch of.
[00:23:38.07]

[00:23:39.19]
A subcontractors after them and.
[00:23:43.05]

[00:23:45.06]
When asked so the website is
how do you know if it's working
[00:23:49.08]

[00:23:49.08]
like are we open a browser and we go to.
[00:23:52.00]

[00:23:53.16]
How could I go and we see this up and
[00:23:56.14]

[00:23:56.14]
then we turn of the news and
see how many people are talking about it.
[00:24:00.17]

[00:24:02.05]
That's terrifying this
is one of the largest.
[00:24:04.14]

[00:24:06.16]
And the should of regardless of where
your politics you know this is one of
[00:24:10.00]

[00:24:10.00]
the largest policy or
initiatives of an administration and
[00:24:13.19]

[00:24:13.19]
it was going to fail because of technology
because a government couldn't figure
[00:24:18.16]

[00:24:18.16]
out how to buy technology it couldn't
figure out how to manage the tech team.
[00:24:23.03]

[00:24:25.00]
And and didn't do any and so
I remember on the last David for
[00:24:30.16]

[00:24:30.16]
President Obama transitioned out he was
with us talking about health care and he
[00:24:34.12]

[00:24:34.12]
said I remember that meeting with my chief
of staff and deputy chief of staff and
[00:24:38.12]

[00:24:38.12]
I asked everyone the room are we green
light everything as everything got and
[00:24:43.05]

[00:24:43.05]
everyone said yes everything is green
all the contractors that they've done
[00:24:46.06]

[00:24:46.06]
all their testing and everything
is greenlit friendly phone but but
[00:24:50.17]

[00:24:50.17]
they never actually tested
the whole thing together.
[00:24:52.16]

[00:24:53.22]
Because no one thought to do that and
that is also the way the nature of which
[00:24:57.16]

[00:24:57.16]
we buy things in the federal government
those you who've worked in the federal
[00:25:00.06]

[00:25:00.06]
government will know this it's a pretty
common story for pretty much every single
[00:25:03.17]

[00:25:03.17]
contractor whether it's your visa
process or your green card process or
[00:25:10.03]

[00:25:10.03]
signing up for benefits of the state
level or signing up for health care.
[00:25:13.05]

[00:25:14.21]
And they just didn't test it and
they didn't have any track so
[00:25:20.10]

[00:25:20.10]
there was a team of my former
coworkers who came out and
[00:25:24.10]

[00:25:24.10]
were like we're just going to spend some
time doing this because we know how to
[00:25:27.21]

[00:25:27.21]
keep a really big system up the big system
with Google search so google search goes
[00:25:32.10]

[00:25:32.10]
on all the time you don't feel it go down
because there's a team of dive ops and
[00:25:36.21]

[00:25:36.21]
authorities and others who are really
really good at keeping sites up so
[00:25:43.06]

[00:25:43.06]
that was the start of this movement in
the federal government United States.
[00:25:46.07]

[00:25:47.19]
That I would call the public one
aspect of public interest tech.
[00:25:51.23]

[00:25:53.00]
Where there were these engineers who
knew how to engineer or design or
[00:25:57.12]

[00:25:57.12]
product manage and
were like my government is on fire.
[00:26:02.09]

[00:26:02.09]
I have to go do something because
my government is on fire and
[00:26:05.11]

[00:26:05.11]
I have the skill set and normal and so
the Department of Defense has actually no
[00:26:10.08]

[00:26:10.08]
software engineering
title in its job database
[00:26:14.19]

[00:26:14.19]
they just don't our government doesn't
have roles for engineers and designers and
[00:26:19.08]

[00:26:19.08]
product managers because that's not what
historically what governments do and
[00:26:22.22]

[00:26:22.22]
they also buy everything outside but
when you only buy things and
[00:26:26.11]

[00:26:26.11]
you have their expertise and how some
manager project you end up getting things
[00:26:30.10]

[00:26:30.10]
that fail over and over again because
you don't know what to buy and
[00:26:32.22]

[00:26:32.22]
you don't know how to manage it when you
buy it and I'll get to why this is so
[00:26:35.21]

[00:26:35.21]
important relevant to you all as well.
[00:26:37.15]

[00:26:39.06]
And one of the secretaries
[00:26:42.01]

[00:26:42.01]
former secretaries in the tech to
carry the United States government
[00:26:45.01]

[00:26:45.01]
is just the head of an agency
the term can be misleading.
[00:26:47.14]

[00:26:49.12]
He joked that if we ask anyone
to build a concrete ship
[00:26:53.15]

[00:26:53.15]
that won't be very useful and
that may ship.
[00:26:56.05]

[00:26:57.09]
May be more likely to think or
[00:27:00.15]

[00:27:00.15]
not be used very often we actually have
a fleet of concrete ships in the military.
[00:27:04.13]

[00:27:05.22]
Someone will build it because we're
paying them a lot of money to do it and
[00:27:08.20]

[00:27:08.20]
if we say we have $10000000.00 It takes
$3000000.00 they will find a way to make
[00:27:12.13]

[00:27:12.13]
a 10000000 dollars That is just how things
work in the United States so you ask for
[00:27:17.01]

[00:27:17.01]
something and people will build it exactly
how you want it and it might not work but
[00:27:20.07]

[00:27:20.07]
people will build it and there's no one
in house until recently who can say.
[00:27:25.00]

[00:27:26.07]
That's not actually how
technology works and
[00:27:29.07]

[00:27:29.07]
maybe you should revisit because
there just wasn't anyone around.
[00:27:33.06]

[00:27:34.20]
So that's the story of one part
of the story of how u.s.g.s.
[00:27:39.12]

[00:27:39.12]
got started there were people probably for
4 or 5 years leading up to the health
[00:27:43.18]

[00:27:43.18]
cannot go scenario this is
a much bigger conversation about
[00:27:46.15]

[00:27:46.15]
movement building in general but in
the fall of ministration who are trying to
[00:27:50.04]

[00:27:50.04]
build up some kind of tech or digital
service being in government for years and
[00:27:54.14]

[00:27:54.14]
they kept trying they tried to
throw the fellowship program or
[00:27:59.12]

[00:27:59.12]
maybe Smalltalk programs and
they kept trying and
[00:28:03.11]

[00:28:03.11]
they learned how the government worked and
they were like prepped and
[00:28:07.04]

[00:28:07.04]
ready for this giant fiasco to happen and
this giant fiasco happened and
[00:28:12.03]

[00:28:12.03]
as with any major disaster you get
like this clear one way to kind of do.
[00:28:16.18]

[00:28:18.14]
Not whatever you want to clear run away to
just kind of bring in people really fast
[00:28:22.10]

[00:28:22.10]
because it had to be done.
[00:28:23.15]

[00:28:24.17]
So we pulled in people who deeply
knew the bureaucracy of government
[00:28:27.22]

[00:28:27.22]
people who've been in government for
a long time career bureaucrats plus.
[00:28:32.13]

[00:28:32.13]
A bunch of private sector
slash people from.
[00:28:35.18]

[00:28:36.23]
The Silicon Valley and
other tech companies under said technology
[00:28:39.20]

[00:28:39.20]
to switch not just to save a life
healthcare dot gov We hate saying we saved
[00:28:44.17]

[00:28:44.17]
it which is like the headline you'll see
in time in Fast Company in Wired Because I
[00:28:48.21]

[00:28:48.21]
feel like no engineer would say that like
that thing was saved is still a total
[00:28:53.23]

[00:28:53.23]
cluster of mangled software
that is held together and
[00:28:58.08]

[00:28:58.08]
every single year we have a team back
out there during open enrollment
[00:29:02.03]

[00:29:02.03]
because it might fall apart
again because it's so fragile
[00:29:05.10]

[00:29:05.10]
because the even though it's not that old
it's built on a pretty fragile system.
[00:29:09.07]

[00:29:11.10]
And so this is movement now and
right now you so
[00:29:15.12]

[00:29:15.12]
we grew that to about 200 people
in the federal government.
[00:29:20.10]

[00:29:21.13]
And then states started copying the model
other countries now have that model we
[00:29:26.03]

[00:29:26.03]
have these get togethers would be call it
like civic tech nerds unite where us and
[00:29:32.01]

[00:29:32.01]
the u.k. and New Zealand and
Australia and Taiwan the and.
[00:29:35.15]

[00:29:36.16]
Estonia and a bunch of other country
Canada all get together and we're all
[00:29:41.13]

[00:29:41.13]
fighting the exact same problems with our
governments where they don't know how to
[00:29:44.01]

[00:29:44.01]
buy technology no one's out to do evil
they just really are terrible at doing.
[00:29:48.02]

[00:29:49.04]
Hiring people to do technology and and so
[00:29:52.06]

[00:29:52.06]
we're in this moment now as you've
seen with broken tech systems and
[00:29:56.06]

[00:29:56.06]
our government has occurred we're
hearing just what everyone uses now but
[00:30:00.02]

[00:30:00.02]
not does occur hearings of hearings at
all tech companies are not equipped even
[00:30:05.02]

[00:30:05.02]
if we have regulation which I think we
should to some extent we are not equipped
[00:30:09.06]

[00:30:09.06]
to do to really enforce our regulation
because we don't have the people around to
[00:30:14.02]

[00:30:14.02]
understand the nuances of if you're
if you say something like the bias or
[00:30:17.23]

[00:30:17.23]
system in some rule what does that
even mean on the technical level
[00:30:22.15]

[00:30:22.15]
people don't know enough in our
government and I also think.
[00:30:27.06]

[00:30:27.06]
That's where schools that have public
policy programs and faculty engage across
[00:30:31.15]

[00:30:31.15]
both sides can really really make
a significant difference no one is leading
[00:30:35.08]

[00:30:35.08]
and that right now Harvard I teach a class
at Harvard Harvard is trying Harvard
[00:30:39.21]

[00:30:39.21]
also it's not leading in it Princeton has
some great programs Ed Felten but for
[00:30:44.12]

[00:30:44.12]
the most part this area for
[00:30:47.06]

[00:30:47.06]
thinking about the direction
innovation is so ripe for figuring out.
[00:30:51.10]

[00:30:52.11]
How to get the right people and
it is a space of technology and
[00:30:57.01]

[00:30:57.01]
policy in figuring out how to regulate
something plus the space of bringing
[00:31:01.23]

[00:31:01.23]
technology into the civic sector to
make sure that we don't have more
[00:31:05.21]

[00:31:05.21]
health care dot gov scenarios there are so
many versions of.
[00:31:11.12]

[00:31:11.12]
The story on a much smaller
scale there is an example of
[00:31:14.22]

[00:31:14.22]
immigration where there was a contract
year contractor who was tasked with
[00:31:19.18]

[00:31:19.18]
building a system that makes it easier for
you to figure out how to apply for.
[00:31:24.03]

[00:31:27.03]
Citizenship for a family member how many
you've had to do that or does apply for
[00:31:30.19]

[00:31:30.19]
citizenship in general it's
a complicated it's a complicated and
[00:31:34.21]

[00:31:34.21]
sometimes people wait for up to a decade
it's really really really complicated so
[00:31:39.08]

[00:31:39.08]
there's a contractor that was hired
to do that after I think 6 or so
[00:31:42.14]

[00:31:42.14]
years they completely failed and
then they won the bid to fix
[00:31:47.20]

[00:31:47.20]
the failure this is just how
the government the u.s. works and
[00:31:52.21]

[00:31:52.21]
so the big takeaway they are with that is
we need more people understand technology
[00:31:58.16]

[00:31:58.16]
in our government everywhere not just
the u.s. all over the world because we're
[00:32:02.19]

[00:32:02.19]
no longer in a world where government
just as government things government and
[00:32:06.22]

[00:32:06.22]
tech are just now in or
weave together whether they like it.
[00:32:10.18]

[00:32:11.22]
Or not so.
[00:32:13.09]

[00:32:14.22]
That's the U.S.D.A.'s side of we have to
[00:32:19.19]

[00:32:19.19]
have people who understand technology
working at all parts of our government but
[00:32:24.12]

[00:32:24.12]
then there's also the very
complex going back to attack and
[00:32:26.20]

[00:32:26.20]
I think conversation it's actually quite
frustrating for me to be around some
[00:32:31.13]

[00:32:31.13]
back in like my tech circles sometimes
where people say things like.
[00:32:34.19]

[00:32:36.07]
We have to boycott a company because it
can't work for the government at all.
[00:32:40.17]

[00:32:41.23]
And to some extent.
[00:32:44.01]

[00:32:45.02]
Yes some of the some of the things that.
[00:32:46.17]

[00:32:48.14]
Some of the things that some of these
government agencies are doing are really
[00:32:51.10]

[00:32:51.10]
really terrible and we should think
about how to not enough those are these
[00:32:56.04]

[00:32:56.04]
are issues that we as us have had to deal
with as well which products we take on and
[00:32:59.23]

[00:32:59.23]
which we don't and I bring this up
because I think it's critical for
[00:33:04.08]

[00:33:04.08]
academic institutions to talk about
this as a weird line between politics or
[00:33:08.21]

[00:33:08.21]
not politics but the end of the day when
we build technology it affects people in
[00:33:13.10]

[00:33:13.10]
it because it does become political If
your technology is being used to to be
[00:33:18.17]

[00:33:18.17]
behind the data system that tracks humans
for a particular purpose for example
[00:33:24.02]

[00:33:24.02]
that this is a conversation that we're
going to have to teach our students to
[00:33:26.16]

[00:33:26.16]
have at it might not be to tell them which
side they're on but it's a conversation
[00:33:32.07]

[00:33:32.07]
that we have to figure out how to have our
students really meaningfully engaging and
[00:33:37.05]

[00:33:37.05]
I think part of the issue we're seeing
with some of these companies is.
[00:33:39.23]

[00:33:40.23]
We're not equipped to have those cards
to even know which other field and
[00:33:44.13]

[00:33:44.13]
expert to bring into the room to help
us how these meaningful conversations
[00:33:47.22]

[00:33:47.22]
is the reason why one of the so
at the great copper conference this year
[00:33:52.16]

[00:33:52.16]
somebody saw that Palin
here was a sponsor.
[00:33:55.08]

[00:33:56.08]
And whole group got
really really upset and
[00:33:59.01]

[00:33:59.01]
they said we have to about boycott
Palin tear because of ice period and
[00:34:03.01]

[00:34:03.01]
there's an uproar and
then Grace Hopper pulled Palin to or from.
[00:34:06.22]

[00:34:08.11]
The list of sponsors and
people congratulate themselves and were so
[00:34:13.00]

[00:34:13.00]
excited while the person that was
the leader of the Grace Hopper
[00:34:18.19]

[00:34:18.19]
conference work for Microsoft and
their Google was still a sponsor and
[00:34:24.13]

[00:34:24.13]
we have to really I feel so strongly that
we have to figure out not just in our our
[00:34:29.14]

[00:34:29.14]
our companies but
with our students these are complicated.
[00:34:34.12]

[00:34:34.12]
Issues that lots of nuance to that
that involve politics and society and
[00:34:40.02]

[00:34:40.02]
ethics that are technologists
oftentimes are not equipped to have and
[00:34:44.12]

[00:34:44.12]
therefore it's easy to make these
statements of this is bad and
[00:34:47.09]

[00:34:47.09]
this is good while also ignoring
the complexity of the situation because if
[00:34:51.06]

[00:34:51.06]
you're going to bark up boycott apology or
you don't have a particular framework for
[00:34:55.02]

[00:34:55.02]
how you deal with issues of sponsorship
and who you take funding from you're still
[00:34:59.20]

[00:34:59.20]
taking funding from other people who
are problematic in the exact same reason
[00:35:05.02]

[00:35:05.02]
why you boycott of this other company but
you would know you're able to ignore it
[00:35:09.10]

[00:35:09.10]
because you don't have a framework for
recognizing this in a broader steps and
[00:35:14.07]

[00:35:14.07]
you don't have a decision
making ability to do that and
[00:35:17.23]

[00:35:17.23]
I actually I think at least in the tech
space many c.s. programs don't.
[00:35:21.23]

[00:35:23.01]
Teach us to do that and even to
know which other fields to bring in
[00:35:27.07]

[00:35:27.07]
our is it the Political Science is
the social sciences is it the race and
[00:35:30.18]

[00:35:30.18]
gender scholars.
[00:35:31.17]

[00:35:33.10]
Going to community members like what
equipping us to make to have these
[00:35:38.04]

[00:35:38.04]
conversations in our organizations and
for those of you who have worked for
[00:35:41.17]

[00:35:41.17]
the big tech companies when
we're making decisions about
[00:35:44.22]

[00:35:44.22]
where to deploy I what to
sell to whom are we serving.
[00:35:47.15]

[00:35:49.02]
It might be different in the a.c.i.
[00:35:50.11]

[00:35:50.11]
sense because that's what you all
do at least in the computing.
[00:35:53.08]

[00:35:54.11]
But computer science degree we don't talk
about that and nuff So I feel like that's
[00:35:59.15]

[00:35:59.15]
those 2 thought that's a multiple not
just 2 sides of the civic tech space we
[00:36:04.17]

[00:36:04.17]
have the yes we half we have I believe
that as technologists we have to go and
[00:36:10.14]

[00:36:10.14]
work in the because if you think if you
care about public service the government
[00:36:13.22]

[00:36:13.22]
is the biggest public service in
most cases of any place you go to.
[00:36:17.23]

[00:36:19.11]
So we have to care about that but also if
you're in a private sector company and
[00:36:24.08]

[00:36:24.08]
you're having the companies are having
these discussions about what is ethics and
[00:36:29.05]

[00:36:29.05]
where you stand there has to be
some kind of framework to help your
[00:36:32.09]

[00:36:32.09]
employees understand.
[00:36:33.17]

[00:36:34.18]
What that really means and and
[00:36:37.22]

[00:36:37.22]
it starts early at least in our education
and I don't think we have that and nuff.
[00:36:43.09]

[00:36:44.19]
Which now leads me to.
[00:36:46.14]

[00:36:47.14]
Something else that I'm working on
which is called the responsible
[00:36:50.19]

[00:36:50.19]
Computer Science Challenge
which Ellen is part of.
[00:36:52.20]

[00:36:54.01]
There is this initiative which was started
by many our network how many folks
[00:36:59.09]

[00:36:59.09]
know of Miti our media our network many so
p.r. middy I was on
[00:37:04.09]

[00:37:04.09]
the founders of e-bay and has since
then moved to Hawaii with his family and
[00:37:09.08]

[00:37:09.08]
has a strong Norma's fund that he puts
in what he called Impact Investing and
[00:37:13.08]

[00:37:13.08]
you can define You can go to the see their
portfolio what impact investing means and
[00:37:19.18]

[00:37:19.18]
they decided a few years ago that they
really wanted to tackle the space of how
[00:37:24.15]

[00:37:24.15]
we educate our future technologists
whatever that means of and
[00:37:29.09]

[00:37:29.09]
over a few iterations where they
landed was well the core c.s.
[00:37:33.11]

[00:37:33.11]
people aren't necessarily paying attention
and nuff So we will put a lot of money.
[00:37:37.13]

[00:37:38.18]
Into computer science undergraduate
education very narrowly recognizing that
[00:37:44.19]

[00:37:44.19]
in the us recognizing that we're going to
miss the international perspective and
[00:37:48.03]

[00:37:48.03]
we're going to miss but I school which
I've been doing this work for forever.
[00:37:52.10]

[00:37:53.15]
And recognize the many people who
will recognize new programs but
[00:37:58.17]

[00:37:58.17]
also some of the people who are doing this
work for a long time for example I know at
[00:38:03.05]

[00:38:03.05]
least here to attack correct me if I'm
wrong and Ellen that you Amy Brenneman.
[00:38:09.14]

[00:38:10.16]
Even Marc does Alan others have been
doing work in what we are now calling
[00:38:14.23]

[00:38:14.23]
responsible c.s.r. ethics and c.s.
for over a decade even.
[00:38:20.03]

[00:38:21.06]
And this recognition that for whatever
reason the rest of computer science just.
[00:38:26.17]

[00:38:26.17]
Says unless it's algorithms or
data structures or theory that's not real.
[00:38:30.09]

[00:38:31.19]
And which is ridiculous and
I felt it when I was here not just
[00:38:37.02]

[00:38:37.02]
those other fields aren't real but
then also other disciplines aren't real
[00:38:40.08]

[00:38:40.08]
where you hear all the time that at least
on the undergraduate level if you're in
[00:38:44.02]

[00:38:44.02]
the College of computing that's real and
are all the other majors are fluff and
[00:38:47.09]

[00:38:47.09]
that's why they have time
to go to football games.
[00:38:49.02]

[00:38:51.03]
Which is also absolutely ridiculous but
we create and then we create
[00:38:56.00]

[00:38:56.00]
this hierarchy of majors right that
definitely exists here at Georgia Tech.
[00:39:00.09]

[00:39:02.09]
But somebody pointed me to how
are you familiar with j.p.
[00:39:04.20]

[00:39:04.20]
Snow's 2 cultures as an essay
that was written a while ago.
[00:39:07.09]

[00:39:09.03]
How would you summarize 2 cultures if you.
[00:39:11.11]

[00:39:15.21]
Want to summarize 2 cultures Yeah.
[00:39:17.13]

[00:39:27.18]
Yeah and there's a line there I
think I'm going to summarize but
[00:39:29.23]

[00:39:29.23]
he's like you know how of the physicist
looks like how do you know under the laws
[00:39:34.11]

[00:39:34.11]
of thermodynamics You must be an idiot and
you haven't the English person let's like
[00:39:39.01]

[00:39:39.01]
how you're not read Shakespeare you must
be an idiot and this idea that there are.
[00:39:44.23]

[00:39:46.09]
Just these different cultures and we
don't push them and I think especially in
[00:39:50.03]

[00:39:50.03]
computer science if you are not the
computer scientist and you haven't done
[00:39:55.05]

[00:39:55.05]
the coding then the algorithms then you're
just not smart anywhere and that's so
[00:39:59.17]

[00:39:59.17]
critical because the goal I remember
is he feeling that at Georgia Tech but
[00:40:04.16]

[00:40:04.16]
then when we go into tech companies.
[00:40:06.11]

[00:40:07.18]
We have the undergraduate computer
science students easily making 6
[00:40:11.00]

[00:40:11.00]
figures of the most valued.
[00:40:12.07]

[00:40:13.09]
The most valued employees by money terms
in the company you're told over and
[00:40:17.23]

[00:40:17.23]
over over again that you need more of you.
[00:40:19.18]

[00:40:21.02]
And and
there's even something that was forever
[00:40:26.06]

[00:40:26.06]
keep with me after working in the h.r.
department was that people were you
[00:40:31.06]

[00:40:31.06]
would hear people say by someone of the
engineer going on in Geneva because people
[00:40:34.07]

[00:40:34.07]
were to say things like well are they
an engineer but in that even in the hiring
[00:40:38.04]

[00:40:38.04]
system there was a field for either
you're either in engineering or not.
[00:40:42.05]

[00:40:44.18]
And that's critical because that goes back
to who has power in an organization and
[00:40:50.09]

[00:40:50.09]
when you've decided that your engineering
organization strickly engineer or
[00:40:54.09]

[00:40:54.09]
his agent has the most power and
everything else whether it's usability or
[00:41:00.03]

[00:41:00.03]
as apology or ethnography or
social science or philosophy is the 2nd
[00:41:05.02]

[00:41:05.02]
then all those perspectives are 2nd to the
technical infrastructure of your system.
[00:41:09.09]

[00:41:11.07]
And I think that has a really really deep
role in some of the broken technology
[00:41:16.06]

[00:41:16.06]
systems that we've built they're built
to scales they're built to reach as many
[00:41:20.01]

[00:41:20.01]
people as possible but not necessarily
built to understand which populations
[00:41:24.10]

[00:41:24.10]
are left out to understand
the complicated political climate
[00:41:28.02]

[00:41:28.02]
of countries that we deploy
it's even in this country and
[00:41:33.08]

[00:41:33.08]
as a part of the recognition with
responsible computer science is that we
[00:41:38.08]

[00:41:38.08]
really have to rethink how we
train our computer scientist and
[00:41:42.17]

[00:41:42.17]
we have to put money and weight behind
recognising that computer science needs
[00:41:46.22]

[00:41:46.22]
this different component in
a disciplinary and integrate computer
[00:41:51.05]

[00:41:51.05]
integrate ethics and responsibilities that
are out the computer science curriculum.
[00:41:55.05]

[00:41:56.06]
And part of that also is to pull in all
the deans of computer science programs to
[00:42:00.19]

[00:42:00.19]
also say hey we as a lot and
all of our industry partners we have
[00:42:05.19]

[00:42:05.19]
an issue letter with as to that something
and she letters matter what a bunch
[00:42:10.06]

[00:42:10.06]
of industry partners are have signed on to
say we really care about this that we're
[00:42:14.14]

[00:42:14.14]
putting money behind this we're paying
your researchers to care about this.
[00:42:18.07]

[00:42:19.08]
And we're going to bring them together and
hope that it makes some kind of a dent in
[00:42:22.06]

[00:42:22.06]
the space and recognize that as take
some responsibility are deeply critical
[00:42:26.23]

[00:42:26.23]
to just all of computing today and
we can't ignore them and the more.
[00:42:30.16]

[00:42:33.02]
Yes please we can.
[00:42:33.23]

[00:42:39.03]
You know.
[00:42:39.15]

[00:42:41.21]
Did you feel that way because yes I know
so and if anyone is ever to Google you
[00:42:45.21]

[00:42:45.21]
are 2nd class and they treat you
that way with her yes if you're out.
[00:42:51.06]

[00:42:52.07]
West.
[00:42:52.19]

[00:42:54.14]
Yep.
[00:42:55.02]

[00:42:59.18]
That's right well throughout.
[00:43:01.19]

[00:43:06.09]
The.
[00:43:07.18]

[00:43:07.18]
Years I will stop there
are no I have 4 calls.
[00:43:14.23]

[00:43:16.15]
From people.
[00:43:17.21]

[00:43:19.02]
Who still want one of you.
[00:43:23.03]

[00:43:24.10]
I will show you where you will.
[00:43:28.10]

[00:43:30.11]
You know all.
[00:43:32.15]

[00:43:34.00]
About.
[00:43:34.12]

[00:43:37.02]
Yeah I know I must go also
works at the tech companies and
[00:43:40.14]

[00:43:40.14]
gets money from other tech companies as
well as an internal conversation that I'm
[00:43:44.05]

[00:43:44.05]
on the result Foundation which to
accept that matters he ought gets
[00:43:48.20]

[00:43:48.20]
as if a nonprofit where he gets money
from lots of different organizations and
[00:43:52.09]

[00:43:52.09]
it's a constant conversation
of where do we get our money.
[00:43:55.03]

[00:43:56.16]
And one of the conditions too was should
already are for a founder of e-bay
[00:44:03.05]

[00:44:03.05]
deeply rooted in tech the funding response
of computer science and now we go into
[00:44:06.09]

[00:44:06.09]
this are they washing their responsibility
and it's a much also bigger conversation
[00:44:11.07]

[00:44:11.07]
we should have at some point maybe not
today about power and money and funding in
[00:44:16.01]

[00:44:16.01]
general I'm part of the Berkman Center
too much as I was telling some folks and
[00:44:20.13]

[00:44:20.13]
I'll get I'll get back on track in the
whole bit which is considered the cousin
[00:44:23.13]

[00:44:23.13]
the mit Media Lab where all the same area
we shall all the same people are hauled.
[00:44:29.18]

[00:44:29.18]
Michael can attest to our whole
environment was dominated by
[00:44:33.01]

[00:44:33.01]
power money funding and Epstein for
probably for September and
[00:44:36.23]

[00:44:36.23]
October and all of that is related.
[00:44:39.21]

[00:44:41.04]
To where money lives who gets the funding
who does the research who gets access to
[00:44:45.06]

[00:44:45.06]
the rooms who make the decision for
this particular challenge the hope
[00:44:50.06]

[00:44:50.06]
is that and again we're all trying this
out there something universities including
[00:44:54.06]

[00:44:54.06]
Georgia Tech and Ellen's work to think
about what it means to and they're great
[00:44:59.20]

[00:44:59.20]
at 6 and responsibility and for some folks
that means taking the algorithms class and
[00:45:05.09]

[00:45:05.09]
while we're talking about edges
the nodes in some graph class
[00:45:09.15]

[00:45:09.15]
also weave in privacy into that class so
that you only think about.
[00:45:13.22]

[00:45:15.22]
The technical part but you're also not
thinking about it in terms of the broad
[00:45:18.14]

[00:45:18.14]
picture of society but also to your point
recognizing that some of us go into
[00:45:24.05]

[00:45:24.05]
engineering computer scientists we think a
certain way we like quantifiable things so
[00:45:28.12]

[00:45:28.12]
where is that medium where you can take
that mindset because there are benefits of
[00:45:33.13]

[00:45:33.13]
thinking in terms of that way too and
applying other ways of thinking to it so
[00:45:39.10]

[00:45:39.10]
that when you're building something with
the very binary mindset you can also now.
[00:45:44.06]

[00:45:45.22]
Bring in your social
responsibility to that somehow and
[00:45:48.22]

[00:45:48.22]
we're all just trying to figure
out what that looks like and
[00:45:51.10]

[00:45:51.10]
a big part of that too and
Hilary Cohen who was integral and have
[00:45:56.13]

[00:45:56.13]
any of you seen the new Stanford cos it's
the one that is there's a new Stanford
[00:46:02.01]

[00:46:02.01]
class they're also are experimenting
that has a computer science professor.
[00:46:05.13]

[00:46:06.19]
A political science and
local philosopher they're all men.
[00:46:11.10]

[00:46:12.10]
And Hillary Cohen is there the main
researcher on that project and
[00:46:18.03]

[00:46:18.03]
her big thing was.
[00:46:20.06]

[00:46:20.06]
We can't just say we want
to live in a world where we
[00:46:22.22]

[00:46:22.22]
train computer scientists to be better and
then they still rule the world and
[00:46:27.01]

[00:46:27.01]
every other discipline is
still 2nd cost us ridiculous.
[00:46:30.13]

[00:46:31.21]
So in addition to training our computer
scientists to better how do we shift
[00:46:35.01]

[00:46:35.01]
the culture to not be just as 2 cultures
of we as computer science know best and
[00:46:41.03]

[00:46:41.03]
everyone else maybe your
opinion will matter later
[00:46:43.19]

[00:46:43.19]
how do we shift it to be a culture of
every time we're making a decision.
[00:46:47.16]

[00:46:48.23]
We have all these perspectives in the
field with us in the role with us as well
[00:46:52.08]

[00:46:52.08]
so I'll give you one example and
[00:46:54.10]

[00:46:54.10]
then I'll wrap up with some of the next
steps on what I think this field is going
[00:46:58.10]

[00:46:58.10]
I run something called the school talk
working group the Berkman Center what that
[00:47:01.00]

[00:47:01.00]
means is off the record I get all
sorts of industry people coming by and
[00:47:04.16]

[00:47:04.16]
just feel like we have this really
gnarly problem what do you think.
[00:47:07.02]

[00:47:08.16]
There's a right to marry an app and
so potentially work for
[00:47:12.06]

[00:47:12.06]
a ride sharing company and
you are passengers and
[00:47:16.17]

[00:47:16.17]
maybe even drivers sometimes
are complaining and complaining but
[00:47:19.12]

[00:47:19.12]
indicating that they don't feel safe being
dropped off in a certain neighborhood
[00:47:23.10]

[00:47:23.10]
of course sometimes you're being dropped
off in a place you know because that's
[00:47:26.10]

[00:47:26.10]
where you go but it's really get a new
cities are being dropped off somewhere
[00:47:29.06]

[00:47:29.06]
you might not know what neighborhoods
like and they're afraid of being unsafe.
[00:47:32.07]

[00:47:33.13]
And the team was like we have
a brilliant idea we are going to use
[00:47:37.02]

[00:47:37.02]
Google Street View and run some algorithms
on them and the side give a safety
[00:47:43.09]

[00:47:43.09]
score and therefore you're dropped
off I'll tell you the safety score.
[00:47:46.11]

[00:47:47.23]
What are some initial reactions to that.
[00:47:49.22]

[00:47:51.17]
Reagan asked.
[00:47:52.17]

[00:47:55.05]
But actually I have quite a few roughly
the equipment is available because it's
[00:47:59.20]

[00:47:59.20]
use that there's there's a precedent of
people using Google Street View for thing.
[00:48:04.19]

[00:48:06.03]
And in.
[00:48:06.21]

[00:48:08.15]
Some.
[00:48:09.03]

[00:48:12.03]
You know so what even so what goes into
a score and if you have only a team
[00:48:15.10]

[00:48:15.10]
of engineers that determines what goes
on the score is probably problematic so
[00:48:18.13]

[00:48:18.13]
we were in this room with some race and
gender scholars a lot like
[00:48:22.08]

[00:48:22.08]
a couple lawyers a few computer
scientist an anthropologist and
[00:48:26.21]

[00:48:26.21]
immediately within 10 minutes
this person was sitting there and
[00:48:29.16]

[00:48:29.16]
really could all have you heard
the broken windows theory and
[00:48:33.04]

[00:48:33.04]
most of your scientists have not
it's a theory that you could go and
[00:48:36.15]

[00:48:36.15]
judge the safety of neighborhood by
how many broken windows you have and
[00:48:39.18]

[00:48:39.18]
it's like been long the bunk for
being terrible and
[00:48:42.21]

[00:48:42.21]
you're like let's think about that but you
can't judge a neighborhood by just looking
[00:48:45.11]

[00:48:45.11]
at it and between like the lawyers and all
these people in there within 10 minutes
[00:48:50.04]

[00:48:50.04]
they try breaking down why
this might be problematic and
[00:48:52.16]

[00:48:52.16]
finally this woman Jasmine McNeely who's
a law professor at University of Florida
[00:48:57.04]

[00:48:57.04]
was like What have you heard of safety or
have you thought of safety for whom and
[00:49:01.08]

[00:49:01.08]
this engineer is person from this Russian
company what do you mean safety for home.
[00:49:05.07]

[00:49:06.19]
And complete and this I think that
question alone completely shifted how they
[00:49:09.22]

[00:49:09.22]
thought about the problem because they're
like well some people might feel safe
[00:49:13.01]

[00:49:13.01]
being dropped off in
Peachtree City some people won't
[00:49:15.11]

[00:49:15.11]
some people will feel safe being dropped
off and not on a lot of people wall so
[00:49:18.19]

[00:49:18.19]
how are you going to term a safety for
whom and they hadn't ever really even
[00:49:23.07]

[00:49:23.07]
thought of that and that sure you can
really train our engineers to better
[00:49:27.07]

[00:49:27.07]
curriculum to think better but also
there's such a benefit of having these
[00:49:31.20]

[00:49:31.20]
different perspectives in the room to
just all the normal like not even bring
[00:49:36.12]

[00:49:36.12]
them a consultant like they're just around
you all the time where you come up and
[00:49:39.10]

[00:49:39.10]
idea in the community challenge
all the time with all these
[00:49:43.12]

[00:49:43.12]
deep deep knowledge they come because
that's their craft on these are all these
[00:49:47.18]

[00:49:47.18]
other people's roles are constantly think
about the societal problems so as we think
[00:49:52.05]

[00:49:52.05]
about this part of the response of c.s.
challenge is yes retrain r.c.s.
[00:49:56.15]

[00:49:56.15]
people but how do we think about
shifting computer science so
[00:50:00.15]

[00:50:00.15]
that these other perspectives are deeply
valued and we're thinking about that
[00:50:04.03]

[00:50:04.03]
with industry too but
[00:50:05.11]

[00:50:05.11]
how teams are structured because Ms Olson
this weird spot of being part foundation.
[00:50:10.17]

[00:50:10.17]
Part funder part industry because it
also makes products like Firefox so
[00:50:15.10]

[00:50:15.10]
how do we shift industry to really change.
[00:50:17.16]

[00:50:18.20]
What that looks like.
[00:50:19.17]

[00:50:21.06]
Yet so I right now a bunch of
companies have rolled open for
[00:50:25.22]

[00:50:25.22]
like some kind of response so you can
probably find them but they're all trying
[00:50:30.17]

[00:50:30.17]
to hire new chief ethical officers or
more responsible engineers or people for
[00:50:36.07]

[00:50:36.07]
the new response and evasion board so
if you're interested in that feels for
[00:50:40.20]

[00:50:40.20]
direct one we don't have enough
students graduating with the skill set
[00:50:45.06]

[00:50:45.06]
while companies need more students so it's
this that we're all trying to figure this
[00:50:49.12]

[00:50:49.12]
out together both from the academic
side and from the industry side.
[00:50:52.21]

[00:50:54.02]
They are basically just want
people who do not exist so
[00:50:56.21]

[00:50:56.21]
if this is your area of interest you
will certain find a home somewhere and
[00:51:02.11]

[00:51:02.11]
there's also a big
movement of figuring out
[00:51:05.07]

[00:51:05.07]
how do we are technologists to work in our
government and some kind of a response
[00:51:10.07]

[00:51:10.07]
a way to make sure our government
services do not failed for the citizens.
[00:51:13.16]

[00:51:15.07]
And with that I'll take I don't know
if I'll take questions on all of this.
[00:51:21.01]

[00:51:23.00]
Thank.
[00:51:26.15]

[00:51:31.04]
You.
[00:51:31.16]

[00:51:37.19]
So.
[00:51:38.07]

[00:51:48.20]
Much.
[00:51:49.08]

[00:51:56.11]
I think that's where from what I've seen
us advice here the tech companies and
[00:52:00.17]

[00:52:00.17]
I'm part of some of these conversations.
[00:52:02.10]

[00:52:04.06]
I hate the term at the pen but it depends
on some of these companies I won't name
[00:52:07.18]

[00:52:07.18]
them but
there's a certain level of management and
[00:52:10.04]

[00:52:10.04]
it's usually like the director level
not the v.p. or senior v.p. or c.e.o.
[00:52:15.03]

[00:52:15.03]
because sometimes they have a buy evidence
of some of their public conversations
[00:52:20.14]

[00:52:20.14]
I don't want that but there's nothing
with the director or slash or v.p.
[00:52:24.09]

[00:52:24.09]
level that deeply want those
employees on their on their teams.
[00:52:28.20]

[00:52:29.23]
And so interview for those teams they've
searched they're looking to change or
[00:52:33.06]

[00:52:33.06]
interview questions like no one has it
right now they're a cop hiring people
[00:52:36.19]

[00:52:36.19]
to help them change their interview
questions to hire more scenes and
[00:52:39.16]

[00:52:39.16]
think about these issues and then yes
there are still other teams a 100 percent
[00:52:43.22]

[00:52:43.22]
don't want people like that too so
there's no uniformity right now.
[00:52:48.22]

[00:52:50.09]
And at some point they're going to hit
an issue where because I think the lever
[00:52:54.19]

[00:52:54.19]
we have in computer science is
are still sets are valuable and
[00:52:58.00]

[00:52:58.00]
if people stop work wanting to go work for
a company
[00:53:00.13]

[00:53:00.13]
then they're going to have to change
how they hire We're not quite there yet
[00:53:03.15]

[00:53:03.15]
because people are still going to want to
go work for Facebook and Google on their
[00:53:07.05]

[00:53:07.05]
I mean I also recognize the privilege
of deciding you don't want to work for
[00:53:10.06]

[00:53:10.06]
Facebook for Google so where at 3 in
the middle of it changing right now but
[00:53:14.06]

[00:53:14.06]
it just really depends on the team.
[00:53:15.15]

[00:53:22.02]
And the students to yeah.
[00:53:23.08]

[00:53:24.12]
So.
[00:53:25.00]

[00:53:27.05]
With the green.
[00:53:28.13]

[00:53:36.06]
You and your year.
[00:53:37.14]

[00:53:38.20]
There was a whole bunch
of Germans I'm right yet
[00:53:41.07]

[00:53:41.07]
build the technology and yes say yes.
[00:53:44.10]

[00:53:46.01]
And I.
[00:53:46.21]

[00:53:48.11]
Hear.
[00:53:48.23]

[00:53:51.14]
What the.
[00:53:53.00]

[00:53:54.20]
Yes reaction.
[00:53:55.19]

[00:53:58.01]
Will be.
[00:53:58.19]

[00:54:00.06]
Like yes yes yes.
[00:54:04.01]

[00:54:07.13]
Yes.
[00:54:08.01]

[00:54:10.22]
You're you're.
[00:54:12.05]

[00:54:16.13]
Great actors.
[00:54:17.06]

[00:54:19.15]
And we've.
[00:54:20.04]

[00:54:21.20]
Yeah so my theories and
I don't know if any of this will work.
[00:54:25.08]

[00:54:26.15]
As I do think as a narrative
point if you were to survey and
[00:54:30.14]

[00:54:30.14]
if we've seen this at some of the surveys
that some of these universities have done
[00:54:34.03]

[00:54:34.03]
if you survey students on that level of
commitment to responsibility to some part
[00:54:38.21]

[00:54:38.21]
of our own like or like our not
wanting to do something terrible
[00:54:42.01]

[00:54:42.01]
like arguably 10 years ago people still
were like We only want to do good that's
[00:54:45.05]

[00:54:45.05]
why we're in computer science but when it
does to your point when it comes down to
[00:54:50.08]

[00:54:50.08]
the unintended consequences or even
a big thing I get from the engineers and
[00:54:54.05]

[00:54:54.05]
students are on our day to day yeah
we get that bias is bad like we get
[00:54:59.07]

[00:54:59.07]
that having our Pop 4 propagate bad
news that eventually the genocide
[00:55:04.12]

[00:55:04.12]
is bad we get that i.b.m. the Holocaust
is bad they are telling us that's bad but
[00:55:08.20]

[00:55:08.20]
was not look like what I'm an engineer
day to day and I'm building software and
[00:55:12.14]

[00:55:12.14]
I'm making these decisions what I'm
picking the language to use when I'm
[00:55:16.15]

[00:55:16.15]
picking what kind of data structures
what I'm picking where to store my data
[00:55:20.14]

[00:55:20.14]
when I'm making all
these decisions like and
[00:55:22.17]

[00:55:22.17]
where does that work and I think part
of it is helping our students think
[00:55:27.21]

[00:55:27.21]
critically at all large steps in at
that lol Of enough of a level plus.
[00:55:34.18]

[00:55:36.05]
We have things in task
like post-mortems and
[00:55:39.11]

[00:55:39.11]
we have way where we analyze problems
where we look at case studies and
[00:55:45.06]

[00:55:45.06]
we there's a postmortem for pretty
much any Kotex failure in a company so
[00:55:50.04]

[00:55:50.04]
how do we have crazy perhaps the same
thing even though I know it's much harder
[00:55:53.10]

[00:55:53.10]
because I'm sure qualitative isn't like at
a point in time Google search went down so
[00:55:57.22]

[00:55:57.22]
therefore we have to figure out what
happens now we're thinking of much more
[00:56:00.17]

[00:56:00.17]
broader society problems but perhaps
thinking of ways to do post-mortems or
[00:56:04.12]

[00:56:04.12]
something similar where it's normal
cadence to review what went wrong and
[00:56:09.03]

[00:56:09.03]
then just not do it again and get
rewarded for it there's like the story of
[00:56:13.07]

[00:56:13.07]
the person who brought the Google
search and got here bonus and
[00:56:15.18]

[00:56:15.18]
that they'd love to tell that story
because it's a thing that happens.
[00:56:18.12]

[00:56:19.23]
And to say that you can raise of
an issue and still get a bonus but
[00:56:25.02]

[00:56:25.02]
obviously with the walk out that's not
true though you can raise that time there
[00:56:28.07]

[00:56:28.07]
are certain issues you can raise and get
a bonus for which is the tech issue you
[00:56:31.03]

[00:56:31.03]
raise other issues and you might be pushed
out of organization so how do we change
[00:56:34.14]

[00:56:34.14]
organizations so that students and people
can speak up so I think we need all those.
[00:56:38.14]

[00:56:39.18]
Parts and yes yes see that night there.
[00:56:43.20]

[00:56:54.22]
You know we should.
[00:56:55.18]

[00:56:57.22]
Be able.
[00:56:59.12]

[00:57:03.01]
Yeah.
[00:57:03.13]

[00:57:11.04]
Well.
[00:57:11.16]

[00:57:14.04]
You know what.
[00:57:14.22]

[00:57:19.09]
Yeah I had a 100 percent see room for
government and
[00:57:24.05]

[00:57:24.05]
the space even hard to get
an example it's not perfect there
[00:57:27.19]

[00:57:27.19]
actually is a joke joke joke joke
by lead to Lars at the moment t.v.
[00:57:31.12]

[00:57:31.12]
I drop all the lawyers are so excited
because now they knew they were good and
[00:57:34.21]

[00:57:34.21]
they're all in these jobs of like
4 companies fighting chiefs are.
[00:57:38.14]

[00:57:39.23]
Which is terrifying I guess.
[00:57:41.10]

[00:57:42.10]
But I I think a dream world and
a lot of folks and Company was
[00:57:46.19]

[00:57:46.19]
a dream world would be for a governing
body that deeply understood technology
[00:57:51.17]

[00:57:51.17]
in the same way that the engineers in
these companies understood technology and
[00:57:56.02]

[00:57:56.02]
they put the same kind of things that they
made that they would do if they were to
[00:57:58.16]

[00:57:58.16]
self govern into law and government but
we don't have that right now so
[00:58:02.19]

[00:58:02.19]
if there was a way if we had people in
government who understood why is it that
[00:58:07.16]

[00:58:07.16]
algorithm has discrimination versus
just that algorithms bias do something
[00:58:12.15]

[00:58:12.15]
about it what takes between that is
not just the data input there's like
[00:58:17.06]

[00:58:17.06]
parts of the algorithm that you're making
decisions on your parameters to but
[00:58:20.03]

[00:58:20.03]
to understand the nuances of what
that looks like looks like and
[00:58:23.21]

[00:58:23.21]
then you make the regulation
based on that and
[00:58:26.11]

[00:58:26.11]
forcing the regulation to sizing
government should have a role but
[00:58:31.12]

[00:58:31.12]
if we were to do that today
we're not equipped to do that so
[00:58:35.12]

[00:58:35.12]
that's terrifying because we're
going to have a bunch of rolls so
[00:58:38.19]

[00:58:38.19]
I'll get share when I get all but
what that can look like too there's
[00:58:41.14]

[00:58:41.14]
something called How many of you know
about the paperwork Reduction Act.
[00:58:43.21]

[00:58:44.21]
There's a thing called the paperwork
Reduction Act in the United States I'll
[00:58:48.01]

[00:58:48.01]
probably do a terrible job and
not a lawyer policy person over there but
[00:58:53.05]

[00:58:53.05]
the general idea is meant that
the government can't keep asking you for
[00:58:56.06]

[00:58:56.06]
the same information over and
over and over and over again.
[00:58:58.06]

[00:59:00.00]
And when we 1st came to the United States
or a service and were in the all these
[00:59:03.19]

[00:59:03.19]
different agencies building out different
tools we're like you can't go and
[00:59:06.16]

[00:59:06.16]
talk to users or people because it's
illegal and like why is it illegal why can
[00:59:10.13]

[00:59:10.13]
I go talk to what you see is because of
the paper Protection Act it's own legal.
[00:59:14.01]

[00:59:15.01]
So what happened was as a scroll
called the Protection Act And
[00:59:17.15]

[00:59:17.15]
over time a bunch of people who didn't
really understand what that meant just
[00:59:21.15]

[00:59:21.15]
chalk that up to you can't
go talk to people at all.
[00:59:24.10]

[00:59:25.14]
Including users of authentic so you can't
go interview veterans just if you want
[00:59:30.15]

[00:59:30.15]
to you can't go in and interview students
who might be using the fast reform and
[00:59:34.20]

[00:59:34.20]
that is a risk of any time a government
that is not understand technology or
[00:59:40.17]

[00:59:40.17]
anything else governing makes a role
we end up with things like that.
[00:59:44.18]

[00:59:46.21]
Were really up.
[00:59:47.20]

[00:59:49.20]
For it.
[00:59:51.02]

[00:59:55.04]
You know one on one where you will.
[00:59:58.19]

[01:00:00.06]
Hear I mean I think a lot of.
[01:00:02.17]

[01:00:03.22]
What I'm.
[01:00:04.10]

[01:00:06.02]
Like about what.
[01:00:06.14]

[01:00:09.06]
Was once.
[01:00:09.22]

[01:00:11.08]
You know.
[01:00:11.20]

[01:00:13.02]
You asked for one.
[01:00:14.02]

[01:00:16.11]
I'll show that I would also love our own
spots too because I was part of that there
[01:00:20.22]

[01:00:20.22]
was a really interesting approach is I
think it's less to be so well and actually
[01:00:26.16]

[01:00:26.16]
bought up learning outcomes with a group
of while ago because she was like there's
[01:00:30.13]

[01:00:30.13]
always stuff going on like what are the
actual learning outcomes and I think it's
[01:00:33.19]

[01:00:33.19]
going to take us a while to even realize
that the learning outcomes are realized.
[01:00:37.11]

[01:00:38.14]
I'll use August an example which I really
like the example of its content but
[01:00:43.03]

[01:00:43.03]
it was taking just core.
[01:00:44.16]

[01:00:44.16]
Computer science work and weaving and
like weaving in how nodes and
[01:00:49.07]

[01:00:49.07]
graph connect to privacy and
I think those are things that
[01:00:53.23]

[01:00:53.23]
it just it makes you really just
internalize what that looks like but
[01:00:58.18]

[01:00:58.18]
there are other examples where people
are pairing social scientists and
[01:01:02.02]

[01:01:02.02]
philosophers and having them come into the
classroom with that's more kind of like
[01:01:05.02]

[01:01:05.02]
a parachuting in Sol Ellen as you
know is doing a role playing game
[01:01:09.19]

[01:01:09.19]
are there others that stand out
feeling that you want to share with.
[01:01:12.14]

[01:01:14.11]
You that.
[01:01:15.02]

[01:01:18.15]
There are a lot of.
[01:01:20.06]

[01:01:22.20]
Work.
[01:01:23.08]

[01:01:27.05]
With the director back here last year.
[01:01:29.16]

[01:01:31.06]
By drought.
[01:01:32.01]

[01:01:34.04]
But you know that.
[01:01:35.11]

[01:01:36.14]
The possibility of them from yeah I know.
[01:01:40.03]

[01:01:41.04]
And.
[01:01:41.16]

[01:01:42.22]
All.
[01:01:43.10]

[01:01:47.01]
But let's think about what.
[01:01:49.14]

[01:01:51.17]
Yeah yeah they're like
yeah they're I think yeah.
[01:01:57.22]

[01:01:59.17]
Yeah.
[01:02:00.23]

[01:02:00.23]
Yeah.
[01:02:01.11]

[01:02:04.21]
I'll share one more than all rap because
they get back to what I mention about
[01:02:07.11]

[01:02:07.11]
localization earlier over at University
of Buffalo basically said my students
[01:02:11.22]

[01:02:11.22]
are the ones who graduate go to Silicon
Valley they stay local They want to stay
[01:02:15.08]

[01:02:15.08]
in Buffalo they're not we're not
like a top recruit for Google so
[01:02:19.21]

[01:02:19.21]
the examples he uses is he ties it to
a cable a local cable company in the area
[01:02:24.19]

[01:02:24.19]
and some of the ethical issues that
come up with the software that the cable
[01:02:27.18]

[01:02:27.18]
company deploys to all of its citizens and
it becomes very personal to the students
[01:02:31.10]

[01:02:31.10]
and they all feel it because they live in
the air they've had to do with the cable
[01:02:34.01]

[01:02:34.01]
company in some manner and
then he brings them down to like that
[01:02:38.05]

[01:02:38.05]
the software that is deployed
in the in the cable company and
[01:02:41.18]

[01:02:41.18]
I think it also is able to a lot of sense
really internalize what that feels and
[01:02:45.23]

[01:02:45.23]
looks like what I think is there really
powerful and with I'm sorry over time.
[01:02:49.11]

[01:02:52.15]
Thanks.
[01:02:54.04]