Library of Congress Digital Strategy

>>Mark Sweeney: Good
afternoon and welcome to today’s LC Digital
Future and You program. Today we’re going to
hear from the Director of Digital Strategy, Kate Zwaard
and her Digital Strategy team. They’re going to update us on
the library’s digital strategy. And the work that they’re doing across the library
to implement it. You know, there’s no place quite
like the Library of Congress. And from whether we’re
talking about the breath of the collections and
the expertise of staff. And I’ve always been
inspired in the possibilities of what we can do in terms
of building the collections, the collecting, the preserving,
and the connecting with people in many different ways. So and as you know,
the library’s vision is that all Americans are
connected to the library. And that our strict
strategic plan lays out a path to become more user
center and data-driven. We’ve charted an ambitious
course to make connections across the nation engaging
and inspiring more people with our unique collections,
expertise, and services. And we’re doing a lot
of work engaging users and enriching their experiences. So as part of this work, we adopted a digital
strategy last year. And The Digital Strategy’s
intended to be bold. A holistic vision that
enables the library to accomplish its mission in
an increasingly digital world. And we think digital
transformation has a lot to do with engaging users and fulfilling the
library’s mission. And we created The Digital
Strategy directorate with Kate Zwaard at the helm to
help lead this transformation. Of course, we’ve been engaged
in digital innovation here at the library for
a very long time. You know, most of us would
think of that, you know, beginning back in the in the
late 1960s with the development of the Mark standard
for our cataloging. You know, in the 90s and
in the early 2000’s we were transforming how
Americans connected to legislative information
through Thomas. And now through You know, more recently
we turned a decades-long partnership with the National
Endowment for the Humanities to expand access to
historic newspapers through the chronicling America. And that’s a partnership
that involves, you know, 50 different states. So we’ve been at this changing
and transforming and connecting through digital technology
in many different ways. And there’s lots of other
examples I could give, but I think those, you know,
gives you the sense of the range of some of the things
that we’ve been doing. So many of these initiatives
involve partnerships and collaboration. That’s both within
the library as well as with institutions
outside of the library. And as you’re going
to hear today, many hands from many
different parts of the library are involved in
creating our digital strategies. So that’s within the library
as well as collaborating with people as well
outside of here. The expertise of the
library staff was critical in creating this
forward-leaning vision. And as we move forward together with our digital
transformation I know that Kate and her team are eager to
collaborate with people in this room and people
across the library. We’re all invested
in one way or another in sharing the library’s
collections and services to engage
the nation. So this is important work. Today, Kate and her
team will update us on The Digital Strategy. And will share some
examples of the work that they’ve been
doing to implement it. It’s wonderful to see these
projects take root and grow. For example, I’m excited about
the projects like By the People. And the potential for
how digital initiatives like the crowdsourcing
program can provide new levels of engagement with our users. And their understanding of the
library by the American people. So I’m inspired to
see colleagues from across the library
working together on this, sharing their expertise, building something new
in the digital space. And the library’s certainly
going to benefit from it. And I hope that you do as well. So what I’ll do now is turn
it over to our Director of Digital Strategy Kate Zwaard. Thanks, Kate.>>Katherine Zwaard:
Hi, everyone. I’m Kate Zwaard, the
Director of Digital Strategy. I’m so glad that so many of
you were able to make it today. Thanks, Mark, for that
really kind introduction. My team and I are here
today to talk to you about how we’re implementing
the library’s digital strategy. Some of you may remember
last year, I’m sorry, last May we spoke to this
group about Envisioning 2025. And we talked about how
the library strategic plan and the library’s digital
strategy are, sort of, working together
to try to vision for the future of the agency. Many of you may know, we spent about a year writing The
Digital Strategy with input from around the library. Last October we released
that digital strategy. And after that, we solicited
an additional round of feedback from staff and from
the general public. And we made a minor update
last year, our 1.1 version. All in all, throughout this
process we incorporated hundreds of edits and ideas
and contributions. And I am enormously
grateful for your good minds, lending your good
minds to this project. I think that The
Digital Strategy as it exists really reflects the
desires and needs of the staff and leadership throughout
the agency. I think it incorporates
a very good balance between being driven by the
strategic plan of the agency, but also incorporating your
feedback and your plans as well. The Digital Strategy
is intended to be sort of a coordinated
high-level articulation of the library’s priorities
for using digital technology to achieve its user-centered
vision in the library’s strategic plan. And now we’re working as a
coalition, the library is, to achieve this vision using
the strategic planning process. So the next step in this
evolution is we spent a couple of months talking to the
library’s planning units. That’s a term of art. That means all of the
units in the library that made a directional plan. So that’s all the service
units, and the centers, and digital strategy itself. Helping them to incorporate
The Digital Strategy in their future plans. And we wrote one ourselves. So now we’re moving forward with
our plans for implementing it. So we have our directional plan. And what we want to
talk to you today is about our next steps
in implementation. Because my team and
I, who are here today, and you’re hear a lot more from
them, feel feel really strongly that implementing The
Digital Strategy means working hand-in-hand with everyone
throughout the agency. So one of the things we’re
going to try to do today is to invite you to think of the
big and small things we can do to amplify digital library. We’ll later invite you to think
about some blue sky things that you’d like to do
related to digital. And now I’ll hand things over
to one of the newest members of our team, Leah
Weinryb Grohsgal.>>Leah Weinryb Grohsgal:
Thanks, Kate. Hi, everybody. I’m Leah. I’m very new to the
library, although not to DC. And I’m very excited to be
here and speak with you today. As Kate said, The Digital
Strategy is a bold vision for the library. It contains three
basic components of what we like to do. And this is how we’re going to be organizing our
discussion today. So I thought remind you
and talk a little bit about what we mean here. The three components are
throwing open the treasure chest, connecting, and
investing in the future. So by throwing open the
treasure chest what we mean, what do we mean? We mean exponentially
growing our collections, maximizing the use of content, and supporting emerging
styles of research. By connecting, we mean inspiring
a lifelong relationship with every visit, bringing
the library to our users, welcoming other voices, and driving momentum
in our communities. And by investing in our future, we mean cultivating
an innovation culture, ensuring enduring
access to content, and building toward the horizon. And these is the way we’ve
laid out The Digital Strategy. So how are we going about implementing
The Digital Strategy? In 2018 we launched LC Labs
to provide a virtual place for experimentation, and to
provide a friendly interface to our more technical side. This year we’ve created a
directional plan covering the next three years. Which is, kind of, as far
forward as we could envision in a pretty rapidly
changing environment. As well as an implantation
plan for this fiscal year. And we’ll do one of
those every fiscal year. So today we’ll ill share some of
the work we’re currently doing in each of these areas. But as Kate said,
one of the things that we are really interested
in is in connecting with all of. Again, we want to hear what
you think the library should be doing in this space. We want to reach out
all over the library to enable our digital
transformation. So after each section
of our talk, we have a short exercise
planned for you. You probably found the sheets
that we left on your seats. And we would love to have
your input however you want to share it. So we have a bowl of
pens that you can use to write down things for us. If you don’t hand it
in today and you want to give any more thought, feel
free to scan it and email it or drop it by to one of us. We have prompts for each
of the three sections. And we are hoping to, kind of, give you an opportunity
to think about it. And maybe discuss a little
bit in between each section. We would, in short, love your
thoughts about where we can go with The Digital Strategy
in the next couple of years. So with that said, I
will now hand things over to the other new member
of our team, Laura Allen, who will begin with the section on throwing open
the treasure chest.>>Laura Allen: Thanks. This is going to be, like,
rapid succession members of the team getting up to talk. So I’m Laura Allen. I am the newest member
of the team, but only by, like, two weeks. So thank you, Leah. I am super happy to be here. As Leah said, The Digital
Strategy identifies a few ways that we want to throw open
the treasure chest, right? Including maximizing
the use of content and supporting emerging
styles of research. So I’m going to talk about
one project that’s designed to do this throwing
open the treasure chest. We were awarded a grant by the Andrew W. Mellon
foundation called Competing Cultural Heritage in the Cloud that we really think will
help maximize use of content and support emerging
styles of research. Before we get into
emerging styles of research, let’s talk about how content is
used in non-emerging methods. That is, how do we
support the use of content in very established
methods of research. At its most basic, the
library support users as they identify
content, access it, analyze it, or reflect on it. And then report on
it in some way. And we have a lot
of infrastructure and deep expertise in supporting
a huge range of activities that rely on this model. Or that support this
model where people want to study an item or a few items. Recently we’ve seen a
growth in research questions that require millions of items. Or that require little bits
from millions of items. What you’re looking at here is from a project called
Viral Texts, which uses the Chronicling
America API as they tried to understand, these
researchers tried to understand how
information went viral in the 19th century
via newspapers. That is, they studied the
reuse of little bits of text across thousands and
thousands of texts. And that method of research
requires a different kind of access than the
kind that we have so much infrastructure
to support. In this case, the API allows
for the access they wanted. This is, of course,
relatively oversimplified. But in the method that
they’re using, text mining, computation linguistics, it can
be called various other things, but it is just one of many. And Chronically America is
just one of many collections that could lend themselves
to this kind of work. There’s also audio analysis
techniques, image analysis, machine learning,
many other methods that require different
methods of access. So let me mention
another example that calls for actually an analytic
method relatively similar to viral texts. This was a request
from a researcher just to do text mining on the
websites of candidates from a recent election. So looking at a particular
issue and how it was represented in the text of websites
over time as events came up in the news how did
camping websites change the way that they reported on
a particular issue. It’s a really methodologically
quite relatively simple. And yet the library was not
able to help this researcher with this question, because we
simply don’t have the analogous tools to make that
content available in a way that this researcher can use it. And so for many emerging
methods we find that the situation is a
little bit more like this. And the reasons are very good. There are many unknowns
about how to best provide infrastructure
for these emerging styles. Creating tools for subsiding
data is really expensive. We want to maximize use and
support these emerging styles, but we want to do it in ways
that are cost efficient, that make sense, that will
actually meet the real needs of researchers. So the Mellon grant. This Mellon grant was designed
to help us learn as much as we can about what
people want. And about how they want
to use our collections. To really maximize use in a way
that helps us learn the most. So basically this green zone
that you’re looking at here, the idea there is
that we are going to create a cloud environment. We’re basically going
to put a lot of data, including digital collections and metadata, into
cloud storage. And then we’re going to
invite four researchers or research teams into
the cloud infrastructure, into that environment, to do
research on the collections on their own computing
or whatever they want. And we’ll see how it goes. We will learn what
infrastructure makes sense to provide. And what they need in
terms of research support. What kinds of expertise do
they need to support them. They’ll just be four of them. So we get to learn a
lot from what they need. And then also what
kinds of tools. And what are some of the
costs and service models that we might develop
out of this. The grant will help the
library develop models for supporting large
computational research and library collections. Practically, it will fund these
four research data experiments using the Amazon
computing infrastructure. It will allow us to hire three
grant-funded staff members to help support this research. As well as providing funds to
help us report on what we learn. I think it’s really
important to call it out that Mellon funded
this project. I didn’t write the grant, so I can say it’s really
beautifully written. Not to set up a program that
we will then continue running forever, but actually to
help the library figure out what we can learn about
this tremendously complicated but absolutely emerging
landscape of research. So the program is
designed to help us learn so that we can create services
and programs and technologies and infrastructure in the future with a bunch more
experience under our belts. So right now it’s the very
beginning of this grant, like, the money came in just now. So we’re getting
ready right now. We’re getting ready
to recruit staff. We’re developing the call
for research experts. And finally, and this
is the one right now where I’m really hoping that the
people in this room can help, like, today, we’re identifying and preparing collections
for the cloud. So I’m going to turn it over
to Jaime who’s going to talk about another project
that we’ve been doing. And then after she talks we’ll
give you the prompt for you to write in that top square box. But for me, I hope that
what I’ve said for the last, hopefully, was exactly five
minutes, will help you think about what collections you can
think of that you’d like people to use in exciting new ways. And what kinds of methods
you think the collections that you know most about
would lend themselves to. What do you think people
could do with your collections if only they had all
the computing power and money in the world? So with that, I will
turn it over to Jaime. Thank you.>>Jaime Mears: Is Jamie
Brezner [phonetic] here? I have your bust. I tried looking for you. That can be edited out. Okay. So another way
that we are trying to throw open the
treasure chest is by funding a program called the
Innovator in Residence Program. And I’m really curious
’cause it’s been around for about a year, raise your hand
if you’ve heard of it before. Whoa, that’s like,
okay, I had bets. Okay. Great. That’s awesome. That’s good. So if you have not heard of
it that is what I was prepared for actually because
it’s really new. So we started as
a proof of concept with two staff innovators. And we’ve only had one member of the public become an
Innovator in Residence so far. And that’s him on the bottom. He’s a data artist
named Jer Thorp. He’s amazing. I’m sure that he got to
interview some of you for his podcast, or you found
him wandering the halls, which he did a lot
when he was here. And I’ll talk a little bit more
about his work in a second. But I want to start by just
framing out what the program is. So the idea is that we
want people to submit, members of the public to submit
two page concept proposals outlining some type of innovative vision
for the collection. And the idea is that their
project will have a ripple effect of access. So whatever they create will
be in the public domain. And then hopefully it will be
something that then, in turn, becomes a way for other users
to engage with our collections and so on and so on and so on. So the idea is that the
work doesn’t stop with them. They’re creating a
tool for other people to engage with our collections. So in order to do
this we need you. What happens is when we
get these concept proposals in we review them. And then based on what the
concept proposal is we tap technical and subject
specialists to help evaluate those
proposals and give feedback. And then the highest scoring
concept proposals are invited to submit a full one. Which I think is
really important, because everyone here knows that
there are some barriers, right? In working in our context. Especially for someone
from the outside. So I think it’s a really
great way to be collaborative, to lean on your expertise,
and to really choose people that we think will be
able to get the thing done that we want them to do. Okay. So what do you mean
when we say innovative? I think this Roadside America
picture is a perfect metaphor. ‘Cause we say this word
a lot, it’s a buzzword. But what I think it
means in the terms of this residency is essentially
someone from the outside that can take their perspective
and make staff and other members of the public see
our collections in a completely new way, right? Completely new. So the idea would be that
if it’s really successful, we actually have no idea, like, what the next innovator is
going to propose, right? So that’s, kind of,
what I think of. Is it a whale? Is it a garage? I don’t know. So an example of this
I’m taking from Jer. So while Jer was here he
was researching the idea of bringing serendipitous
discovery back to large-scale digital
collections. He wanted people to
engage with our collections without having a specific
research question in mind. And he did this through
a podcast called Artist and the Archive. And he also did this
through a series of proof of concept applications
that are on our website. So this one that you see
is called Library of Color. And what you’re seeing here is
our Mark Records Collection, which we made available
around the same time that Jer was onboarding. And what you’re seeing
are visual items. They’re Mark records
represented as a color spectrum, that if you were interacting with the application
you could scroll over, and it would represent, you
know, hundreds of items. And sometimes it’s pulling
descriptions of those items. And sometimes it’s
pulling the title. And each of the items
is mapped to a color. So how did he do this. He did this with a
totally open crowdsource. There’s a fan. Yeah. A crowdsource
data set online. It’s a color dictionary
that was created by the XCD web comic author. And he put a survey up online that over 221,000 people
answered where he presented them with a color and he
asked them to name it. And there were 5
million colors named. So Jer took this crowdsourced
data set, and then applied it to color words in
our collection. So for this specific one, you see in this William
Hogarth engraving dealers in dark pictures. So I got this because dark
someone saw as this, kind of, like, it’s black to me. I don’t know what it is to you,
but it’s, like, a black color. It’s dark. It’s hashtag 1B2431. And that is how it ends up here. So I’d invite you to
check that out if you can. So this application, like a
lot of the ones that Jer did, not only upends traditional
paradigms of the way that we think about search. But he also was literally
injecting what I think of it is, like, a cacophony of public
voices, and the way that members of the public names things. And, kind of, like, mashing
them together with the way that we ourselves have
described things, like, very formally in Mark record. And I love the dialogue
that happens in this. He did it for a lot
of his collections. Okay. So I am very, very
pleased to announce — The press release
has not gone out yet. But we have two innovators. We’re playing with a cohort
model for fiscal year ’20. Our innovators for fiscal year
’20 are Brian Fu and Ben Lee. They were actually here
last week onboarding. This is Brian talking
with some NBRS people. And his project is going
to be called Citizen DJ, where he will collaborate
with library staff to identify sonically
interesting and culturally relevant audio
and moving image collections that are free to use for
sample-based hip-hop production. So by embedding these
materials in hip-hop, he’s hoping that listeners
will be able to discover items that they never knew existed. It’s going to be so cool. And then Ben, I don’t have his
face, but you’ll see him son. Ben is going to be
applying machine learning and computer vision to
basically extract images from Corpora [phonetic]
at the library. It might be one library
collection. It might be multiple. I’m not sure. This is an example of
a possible workflow with our Chronicling
America collection. Where he’s extracting an image, the computer is labeling
it horse, person, whatever. And then he organizes those
images based on likeness of what is inside of the image. So the idea is that we will
have some image data sets. And then we’ll have
a visualization where people can browse by image
at the end of his time with us.>>What is Corpora?>>Jaime Mears: Oh, sorry. It’s actually a word
that he was using a lot that I’ve just started using. Where it’s, like, a
corpus of things, like, things that come together. That’s what I think
of as a Corpora. Mm mm. I guess Corpora
is multiple corpuses. Which we’re hoping that he’ll
do more than one collection. So that’s why I’m
saying Corpora. So if you did not meet them
last week they are coming to the holiday party. And I’m going to be
bringing them around. So hopefully you’ll be able
to meet with them in person. And if not, they’ll
be presenting the week of December 9, about
their projects. Probably in West Dining
Room or something. So we’ll put that
announcement in the Gazette. Okay. So now you’re
going to talk. So we didn’t know — I don’t
know, it might be weird because you don’t have
something to, like, put your thing on,
but we have pens. Abby Potter has pens. So we are really interested
in the next 10 minutes in having a conversation
about what your ideas are. So what would you
like, how would you like to see the library throw
open the treasure chest? And we really see
your responses, kind of, running a spectrum. They can be directly related to
your work, your specific area of expertise that you have. You know, is there some idea that you’ve been thinking
about, like, for a while? Or do you have a big
library-wide idea that’s, kind of, been in your back
pocket and now’s the time to let it out, you
know, in a healthy way. So, yeah, it’s not very serious. We hope it’s fun. There’ll be five minutes
for you to think and write. And then five minutes
where we’re hoping that we can just
hear some ideas. And then hopefully we’ll be
able to collect the worksheets so that if anyone doesn’t
have a chance to speak.>>You can put your
name on them. And then if you want, there’s
probably a blank one near you. So if you want a version with
your name and a version without, you can probably do both.>>Oh.>>Just saying.>>That’s so innovative. Okay. Yeah, so I’m not
sure what time it is, but we have five minutes.>>Meghan Ferriter:
Okay, this is the best. We love hearing you
laugh and chat. But we actually cut
our 10 minute short, so we can share a little bit
more and do some more exercises. So please continue
writing if you’re writing. I’ll try not to distract you
with what I’m going to say. I’m Meghan. I’m also part of the team. And our second goal in The Digital Strategy
is we will connect. So really this means making our
incredible programs, services, content all available and
accessible, available to and accessible by Congress
and the American people. So I’m going to share a little
bit more about some of the ways that we are working to
connect with everyone through our communications
approaches. So it’ll be a bit
of broad strokes. A few specific things. If you have questions,
please come find me, be happy to share more. If you have ideas to
collaborate, we love learning from our community of
practice here at the library So using our blend of
communications vehicles, we’ve really tried
to build bridges to help create understanding about the library’s
Digital Strategy. And also the work that
we’re doing every day. So I’m going to take
a few minutes here and share a little bit more about what we did
in the last year. Spoiler, we were very busy. And the ways that we spent
it growing our network and trying new communications
approaches, showcasing our work, and amplifying that of our
colleagues, and connecting with others through our work, and a range of different
approaches. So through a number of touch
points, we really tried to stitch together approaches and harness the incredible
resources we have to share here at the library. So that includes the
content, services, and programs in which you work. And the work that we’re doing
to facilitate different uses of our collections, or new
ways of approaching the work that we’re doing
here at the library. And we share our work through
channels, like, our website, the signal blog,
Twitter, and our Listserv. But also through our internal
networks here at the library, such as The Gazette,
forums in Listservs, open houses, town halls. And our brown bags and working
with our community of practice who are sharing their
approaches as well. And then we reach further to
our peers and new audiences through conferences
and hosted events. So with all of these
interconnected communication channels, I often, kind of,
call this our ecosystem, we hope to build stronger
ties and stability that help us take the next steps in moving toward inspiring
lifelong relationships with the library. So from our metrics,
we have evidence that we have done
an okay job anyway. We’ve maintained
steady engagement with our visits to the website. We have many increased downloads
of data sets and the reports that we share on our website. But we also know from
qualitative measures that our peers and other
organizations are actually trying some of the approaches
that we’re trying as well. So that includes creating spaces
such our LC for Robots page so — – And actually doing
a little bit of a better job than us in creating
computational access to resources. And also other folks are trying and leveraging the Jupiter
notebooks that we’ve created for use of content, such
as derivative data sets that we share on our website. So most of our work really in
our communications approaches is about illuminating the
work of our colleagues who are stewarding and making
available our incredible collections, metadata, and
authoritative information. What we’re able to do
is really only possible, and what we’re able to
facilitate is only possible because of your work
and the work of our colleagues
here at library. So we aim to use our
communication channels as a window through which
people can gain a view into what is available
to all Americans in the Library of Congress. And if we approach our work in
this way, we really are going to make great strides in bringing the laboratory
to our users. In The Digital Strategy this
approach is really encouraged. Quoting now among our
most important treasures at the library are the knowledge
and wisdom of our staff. We will empower our staff
with tools and pathways to make it easy for them to
share stories, standards, expertise, and data with the
broadest audience possible. And we want to use our
opportunities in communicating across our many channels
and in our ecosystem to really communicate
with this spirit in mind. And so far it’s working. So for example, last year
we hosted two Twitter chats. Jaime showed a picture
of our serendipity run with our innovator in
residence Jer Thorp. And we also hosted a web
archiving Twitter chat to draw attention to newly
available web archives derivative data sets. And highlight our
incredible web archiving team and the practice
here at the library. For example, during the
web archiving Twitter chat, we sent about 28 tweets
over the course of 3 hours. That sounds like not that much,
but when you’re typing it live and making it go the time flies and we had great fun
during that time. But we reached over 52 and
a half thousand accounts, and we made nearly 290,000
impressions on Twitter users. And that’s a pretty big
impact for a quick amount of work in a three-hour chat. We also live Tweeted events
that we were attending, including those we hosted,
like the Machine Learning and Library Summit and the Arts
and Humanities Research Council, UK, US, Collaboration Workshop. And we went behind the
scenes here at the library. We highlighted preservation
and conservation. And we rode along with
innovator and residence and made that available to
people as they were, kind of, following as well. And then we went, as we
mentioned we go to a lot of events and meet people
who are practitioners or who are looking
into similar approaches that we’re using
here at the library. As we cohosted a data jam at
the Association for Computers in the Humanities during which
participants created new apps and visualizations
using library APIs. And of course, we continue to
collaborate on the signal blog with the digital content
management section of DCMS. And through the signal we
continue to publish blog posts that illuminate practice,
lessons learned, and encouraged more questions. So finally, we continue to aim to bring people together
digitally and in person to share and learn from one another. As The Digital Strategy
states, a traditional strength of libraries is a
willingness to work together. When we collaborate, we can achieve together what
we cannot accomplish alone. And that is a really strong them through our communications
approaches as well. So as you’ve heard, seems like the word connect
is definitely a buzzword in our presentation today. But we really do want
to hear from you. So please get in touch with us. This year we want to improve the
ways that we share information, opportunities, outcomes,
and our progress towards The Digital Strategy. And we’d like to hear
from you about the ways that you find information. So not just from us, what are
the methods or the resources from which you gather
information. And how do you find out more
about what’s happening here at the library as well as
in your professional sphere. So I’m going to hand over to
Abby Potter, my colleague here. And we’ll be back to
chat with you in a bit.>>Abigail Potter:
Thank you, Meghan. And as Meghan talked
about connecting with communities is a big
part of The Digital Strategy. And part of that work
is translating the needs and opportunities in
The Digital Strategy. And from the experience and
pilots that we undertake to different communities. And connecting to committees can
meet a lot of different things. A big part of the experience
we do is learning more about the nontraditional
users of the Library of Congress, or sort
of new users. We want to explore
new ways to reach and engage scholars
using digital methods. Artists like Lori
and Jaime described. We’re also interested in
learning more about how to engage with the
general public and underrepresented
communities. And how all these different
communities can be present in the library today
and in the future. So we also want to connect with our existing
partner communities. So end-users and in this
we’re including the staff of the Library of Congress. And we want to deeply understand
the needs of our, sort of, existing partners and
what drives momentum in these communities that
we’re already partnered with. Both of the categories of
user communities, the new and existing have
a lot to offer us. And part of The Digital Strategy
and the overall strategy of the library is to
create an environment where all communities are
inspired to engage with us. And today I’m going to talk
specifically about engaging with expert communities. All the people in this
room together here are part of an expert community. It’s a community of staff. You all know very, very well
how this institution works and how it can be improved. And you’re all very passionate about what you contribute
to the library. And we as lab’s team are trying
to explore different methods to harness and capture
this expertise and passion to help achieve The Digital
Strategy and the vision to connect all Americans
to the public. All the public to library. So this is a very oversimplified
drawing of, sort of, what a labs process is. And I circled staff ideas
’cause that’s what I want to focus on here. But we have things coming in,
ideas, services, questions. We go into the lab. There’s collaboration,
experimentation. We try new methods, processes. We talk to a lot of people. And we develop new
pathways of doing things. And then outcomes, I think
it’s important to see that not everything that comes out of the lab is a
tool or a digital thing. It’s services, methods, skills. Those are, sort of, the things that often make the
most difference. This diagram came from a book that was recently published
called Open a Glam Lab. So if you have been following
the Signal or Twitter, you might have noticed
that we took part, I took part in something
called a Books Sprint. A Book Sprint is a
rapid publishing model. It’s a method that’s been around
for about 10 years that came out of the open source
software movement. And where’s where a group
of people, no more than 15, get together and share their
knowledge and perspective. And they write a
book in five days. So this is something that I
did the last week of September. And the book was published,
I don’t know, last week. So it was a very rapid process. But it was also really
interesting. It was intense and it was fast. There’s no time for extensive
research or wordsmithing. So really brings the
tacit knowledge out. So the kind of thing
that you would share in a hallway conversation. And try to get that knowledge out of people’s brains
and onto paper. It was a great process
for producing something from a collective
voice and perspective. It was a facilitated process
so no one voice dominated. And there was an
extensive, sort of, reviewing and rewriting process. And the book itself
it came out great. It really articulated why new
ways of approaching the work of galleries, library,
archives, and Museum, that’s what the GLAM stands
for, why having these, sort of, experimental spaces is
important to when we’re looking at what to do in digital. And we see a lab as a place
where you can provide space to be you can be open
to experimentation and risk-taking and iteration. And this theme is also, sort of, what the Book Sprint
is all about. This is the map of, sort
of, representative of people who participated
in the Book Sprint. It gathered expertise
from around the world. And the expertise was really
important to write in the book. But what the process
also required was for the participants to be
vulnerable and open to critique and able to accept other
people’s perspectives. So this process it was
difficult, but it did create, you know, a book length
publication in five days. And it also really
bonded the group together. And positioned it to,
sort of, do even more. That small group was
representative of a larger group that is calling itself
a GLAM Labs Community. It’s about 60 institutions
from about 30 countries. And some of them are on
the map, not all of them. And you’ll see there’s one
little dot in North America. And that is us. That’s the Library of Congress. And to hoping to build on this
momentum we’re going to host as part of the Collections as
Data series in May we’re going to host this group at
library to try to think about what’s the next big thing
that this group can do together. So you can find the book at
Gamlabs.IO, Glam Labs with an S. Or you can find it
from our website under our Report section. Okay, so now we’re
here at the exercise. So you saw that some
impactful work can happen that aligns The Digital
Strategy without one line of code being written. I think we want to underscore
the fact that a lot of the, sort of, experimentation, innovation that we do
is not, sort of, coding. It’s a lot of process work. But we’re interested
in trying out a lot, a method that’s similar
to the Book Sprint where we can focus
intensely on a specific topic over a restricted amount time
to draw out the expertise from the people in the library
and cross pollinate ideas. So we’re borrowing
language from what Lori and her colleagues have come
up with of when she was at Penn around something
called a pop-up lab. So there’s some proposals,
kind of, floating the library right
now about doing a pop-up lab about a specific, sort of, idea. But we want to ask you, how
would you use this method. And what, sort of, topics
would you like to explore. So the exercise that we have in the second boxes
we’re asking you to, if you were given a
whole week to, sort of, work on one gnarly problem,
what would that problem be? And it might not be a problem. It could be an idea. What, sort of, you know, what
do you think just needs an extra push or some extra
examination to, sort of, get to the next level
to, sort of, propose. Maybe to propose an
experiment with labs. Or to propose something else
over a different channel. So that’s a question. And you have that
space to fill in. We’re interested in, sort
of, your ideas, and also to, sort of, figure out
if this, sort of, pop-up lab idea would
work, sort of, on a borrow [phonetic]
scale so — Yes. Oh, yeah. Yeah, but five minutes
’cause we’re running a little bit over. So five minutes to
write down your idea. Start now. Okay.>>Eileen Jakeway: Hello. Alright. Hey, everyone. Thank you so much for
willing participation. I am Eileen Jakeway. I’m an innovation
specialist with Labs. And I’m kicking off the third
part of our plantation plan, or sorry, Digital Strategy,
which is to invest in future. Which is, kind of, an overwhelming prospect
if you ask me. So what I’m going talk about for
the next three to five minutes that I have of your time
is machine learning. Which is a new technology,
well, a technology that we have, sort of, been investigating
for the past several months. And you’ll hear more about the
specifics of a project later on from Meghan and Abby. So I want to just start
just, kind of, for my sake, and hopefully for someone
else’s in the room as well, asking the question what
is machine learning. Because in a way the name of the technology is
a bit of a misnomer. Because really it’s not
machines doing all the learning. It’s very much a work of
human labor that entails as much human intervention as,
like, coding website, right? So in its most boiled down form, machine learning is
essentially training computers and computer algorithms
to recognize patterns across large data sets, right? And then the second part of this
slide is using those patterns to make sense of the new maybe
previously unseen data set, right? So sometimes that includes
supervised learning in which humans are actually
intervening by labeling or segmenting data And
so I wrote down here, because I wanted to really
say it to this group, that as professionals whose work
entails identification, right, and categorically structuring
data on a daily basis, you’re a crucial
part of this loop. So I wanted to give
a brief example. And I’m sorry if it’s
a little juvenile. But essentially if I have a data
set consisting of dogs, cats, and I think I wrote
elephants down here, I go through in my training
data and I label all of the cats as cats, right? So presumably now, the algorithm
will have been sufficiently trained to pick out all
of the cats in a data set that it hasn’t seen before by
looking for visual features that it now believes a
cat to possess, right? So this is actually pretty fun. This is images from the
library’s collections of free to use image sets. The image on the
left would be a cat. And the image on the right would
be not a cat or an ostrich, according to the
caption of the picture. And I’m hoping one of
you can maybe explain that to me at a later date. Because I actually think this
picture would be really hard for a machine learning
algorithm. Because the caption
underneath reads that it also has very
particularly un-goose-like features, feathers, sorry. And so I don’t know
what that means, what an un-goose-like
feather looks like. But I think you have
it on the screen here. So why, might you ask, is
missing learning relevant to libraries and to this
library in particular? Well, I think, you know,
part of that is throwing that question back to you in
terms of people who have a very, very intimate knowledge of taxonomies using
library settings and labels and structures of
data that are helpful for exploration and discovery. But I do know a little bit
about how other libraries, and this library in some ways,
is using machine learning for a series of tasks. So some of them are
up here on the screen. I don’t want to bore you
by reading all of them. But thinking about identifying and extracting types
of content, right? So visual content
versus textual content. Being able to generate labels
and tags that actually increase and enhance discoverability by
being entered in as metadata or used in discovery tools. Doing quality assessment of some of the digitized
collections that we have. And maybe even being able to identify subjects
in photographs. So on September 20, this
is the same blazer, okay, so you were wondering,
we hosted a conference that essentially convened
around 75 professionals who are combining
cultural heritage and machine learning
in some way. So the purpose of the summit
was in part to actually run a, sort of, survey of
what are people doing and how could we potentially
be using this technology. So I wanted to just showcase
three quick examples that came and presented at
this conference. Because I think their work
demonstrates some of the uses that might be the most
applicable for you in your work. And hopefully will, sort of, prompt further ideas
from the group. So the first is called the
Civil War Photo Sleuth Project. I don’t know if some of you
have heard of this before. It’s based out of Virginia Tech. So not too far. And the core purpose
of this project is to identify the soldiers who
were in I think over 40,000, 4 million, excuse me, portraits
of soldiers from the Civil War. So it’s a combination of crowdsourcing and
machine learning. So essentially the
process, I’m sorry, I didn’t realize this
is cutting into my time. So essentially the process is
they have created an archive using materials from the
library’s collections and other major cultural
heritage institutions. But also from private
collections. So allowing people
to actually upload and share pictures
from their family. Or from their local library. Or from other places where we
might not already have absorbed these materials. Mapping, sort of, doing
facial recognition software to map the reference
points on someone’s face against the reference points in
a database that we already have. So whether that’s people
who’ve already been identified in other archives. Or whether that’s through
crowdsourcing by people going in and actually manually tagging
people and their identities. So that’s, kind of, one example. A second example was actually
a project that took place here in DC at the United States
Holocaust Memorial Museum. So the lead on this project
is Ben Lee, who is also now, as Jaime mentioned, one of our
current Innovators in Residents. And his problem was one, I don’t
know if you’re familiar with it, but essentially was
one of searchability. Because he was interested
in looking at the reference cards held
in the central name index of the International
Tracing Service. So these are reference cards
that actually point back to death certifications
that were, sort of, issued from people in the concentration
camps in the Holocaust. So problem is, these reference
cards are interspersed with the other 39 million
items in the index. And so Ben used essentially
machine learning to train an image set on what
is a death certificate reference card and what is not, right? So his training set, I wrote
this down because I did not want to lead you astray, was 22,117
cards that he hand labeled. And he got his algorithm to be
so effective that he was able to run it over all 39
million scans in the index and retrieve 312,183 death
certificate reference cards that were previously
only indexed by name. So there is an article that I’d
be happy to share if you want to know more about
the specifics of that. Or how that, kind
of, worked out. Actually, you can ask
Ben when he’s here. And then lastly, this is a tool
that is currently in the making at the Smithsonian
Data Science Lab. So also pretty local. And they’re using
machine learning to identify duplicative images on their hardware
and network drives. So using a hash algorithm to,
and I’ll confess this is, like, the one that I probably know
the least about technically, but to essentially, like,
run a series of the hashes against the databases
that they have to see where they retrieve
identical hashes. So it’s essentially, like,
compressing an image to see where there are duplicates. And whether or not
that was intentional. And which one is higher quality. So that’s just to
get you, kind of, thinking about machine learning. I hope it was instrumental
and you learned something. And, yeah, I will hand it
over now to Meghan and Abby to talk more about a
particular project that we did. Thank you.>>Meghan Ferriter: We’re back. So we’re going to share a
little bit about a project that has been ongoing
since July. And we’ll wrap up
actually in January. But tomorrow we will hear
some in progress results from this team at the
University of Nebraska Lincoln. So we were interested, as
Eileen mentioned, in what began as a summer of machine
learning and has turned in, blossomed into a season
of machine learning. We wanted to really
know about the ways that machine learning processes
work on library collections. And what information
could be created. As well as directions
or indicators for machine learning applied
to our collections broadly. So to move forward on this idea,
we created a statement of work. And we released a
request for proposals. And specifically, which seems
to maybe be a little different than these processes,
we really wanted to hear about how it works
inside the black box. So rather than just asking
for a full-scale solution, we wanted a research
collaborator who would partner with us, help us to codesign,
and make decisions together. And also understand from
a professional perspective in a computer science
profession perspective, why and how decisions are made with using certain
types of material. So we were very fortunate that
we put the contract out for bid. And we received a proposal
from the University of Nebraska Lincoln and the
Project Ada [phonetic] Team, who’ve worked closely with
Chronicling America content and identifying poetry
content within newspapers. And we worked with them and
they, within their proposal, articulated a plan of research
that would address our goals. And also result in a
prototype of report, collaborative research
design, and research support for two graduate students. And then we had — And
that was Doctors Liz Lorang and Leen-kiat Soh. And we had doctoral candidates
Mike Pack and Yi Liu come to work with us on-site
at the library for six weeks before they
returned back to Lincoln. And they said they
really enjoyed it because they had the freedom
to focus on just the work and, kind of, get lost
in collections. So the project in
total is 21 weeks. But throughout the process,
since the start of July, we’ve been having weekly calls
and now biweekly calls to, kind of, check in on progress
and to answer, to questions to connect Mike and Yi with
staff here at the library from across library
services and OCIO. And they really began
working pretty quickly with what was available from the
library’s API, APIs, excuse me, and they specifically
were looking at digitized newspaper
content, handwritten materials, and rare book content. When we started this process
we also had a kickoff meeting. And we really discussed some of
the possibilities and concerns of applying machinery
to our collections here. And so were chatting
about things such as improving
discoverability of resources, wanting to know how machine
learning can help us learn more about our collections. So leveraging the work again. I mentioned earlier leveraging
the work of staff in this space. And some good discussions around
the apprehension of how to deal with bias in the
data and the ethics of using these technologies
in our spaces. So as we moved forward, Mike and Yi designed five small
projects in just six weeks. It took about a week and
a half for each project. And their goal was with
their time on campus here at the library to get
enough of progress on each of their products that
they could go back and iterate on those in Lincoln. Which they did successfully. And I also gave them the bid
with less than 24 hours’ notice to give us a presentation
the day before they left. And they nailed it. It was really incredible. So some of the things
specifically that they are focusing on. This slide is shared
via link cat. So this presentation at our machine learning
and libraries event. And in essence the main
approaches that Mike and Yi are exploring
in their own research, and so they brought them
to bear on this project, are segmentation,
figure extraction, and image quality assessment. And in essence what
they were able to determine pretty quickly
is that they, we had wondered if they would be
able to use some of our crowdsourcing
content as a training set. So from our Beyond
Words application. And it turns out that that
was not clean enough data for them to use. So great finding for us. And makes a lot of sense since it was not
designed for that purpose. It was designed to help
augment and caption images. They were able to use the
European Newspaper Project as training data. And one of the really
exciting components is that they were able to transfer
the model that they created around newspaper content
to rare book content for figure extraction. And the demonstration
of that showed that just with a little bit of extra
training, they were able to really refine that. They also explored
several models to determine which would be the best to use
for these particular approaches. So as you can see
here in this slide, it’s pretty small actually,
so I’ll read to you. They were working on
document segmentation, figure and graph
extraction, text extraction from those spaces, document
type classification. And in the document
type classification, this is specifically
working with material that is currently presented
in the By the People Project. And they were able to, kind
of, determine some ideas about complexity of
those materials based on basically density of
text within those images. And then they also were able
to do some quality assessment of the images that are presented
in Chronicling America. And create a few
preliminary recommendations around the feasibility of
using those collections within some of these models. It was a pretty exciting
outcome for us. And one last thing to wrap up, that we will be sharing the
results of their project openly on our website when we
receive them in January. And if you have other
questions we would be happy to answer them.>>Abigail Potter: I
want to say one thing.>>Meghan Ferriter: Yeah.>>Abigail Potter: And then I’m
just going to wrap up that by, sort of, mentioning the summer
of machine learning theme that we were talking about. That is a theme of doing an
experiment, having a meeting, doing an internal experiment. That’s a sort of way that we’re
thinking about tackling these, sort of, more forward horizon
issues, like, machine learning. We’re thinking about different
kinds of, applying these methods to different content, like,
AV or maps and what, you know, what would the experiments
around that be. You know, what would different
events or different, sort of, conversations that we could have
around those different formats. So I just wanted to call that
out that there’s this, sort of, seasonal learning is to move
us along on reaching our, sort of, horizon goals. So that we can, sort of,
work with you all about how to operationalize these ideas
and the things that we learn.>>Meghan Ferriter: So we are
now into our third exercise. You can turn your sheet over
and find a new blank field. So we’ve shared a lot
about some of the things that we’re currently working on. And we have wonderful hallway
conversations with you all about ideas that
you’re interested in. But we really would like
to hear from, you know, what is the most exciting
thing you can imagine the library doing. And then associated with that,
what would it really take to make that possible. So this is an opportunity to
engage in some blue sky thinking with maybe a little bit
of practicality, kind of, tucked in there as well.>>Abigail Potter: And you don’t
have 20 minutes, you have five.>>Meghan Ferriter: Yes.>>Abigail Potter: So –>>Meghan Ferriter: Sorry. Moving quickly.>>Abigail Potter: And then
we’re going to come back. And we’ll do some QA or
little wrap up and QA.>>Meghan Ferriter: And
a little bit of a preview of the next LC’s Digital
Future and You as well.>>Abigail Potter: Okay.>>Lauren Algee: Hello. So hi, I’m Lauren Algee. I’m the final member
of the Labs team. And I’m one of the community
managers for By the People, the crowdsourcing program that just celebrated its first
anniversary here at the library. So to circle back to
Mark’s introduction, you didn’t hear anything
about By the People yet today. And that’s because we’re having
an entire other Digital Features and You about crowdsourcing
next month. So you have to come back. But I will quickly throw
some numbers at you since we celebrated
our birthday. And we’re really excited about what we’ve
accomplished in our first year. So in one year of By the
People, which looks like this, we’ve launched 11 different
crowdsourcing campaigns. We’ve had over 11,000 volunteers
register with the site. And many, many more have
contributed anonymously. You don’t have to register. Thirty-four thousand pages have
been completed in the last year. We have another 56,000
waiting review, peer review, also by our volunteers. And 8,000 are back in So that’s just a teaser. And I have two final
assignments for you, though, before you can leave
and before I had it back to Kate to close out. And then we can answer
all of your questions. First, you have to
go try By the People. How many people in this room
have tried By the People? Yay. Those of you who haven’t, I’ve noted what you
all look like. But especially, you know, I hope that you’ll come
back for next month. But if you do we
really, you know, it’s going to be much
more fruitful for you if you’ve given it a try. And we can have a really great
conversation about its future and things you might think
would make it better. And then also there’s one
final little panel on your card that will help us shape
next month’s program. Which is write down one
question that you have about By the People as a
program, as a platform, about crowdsourcing
at the library. And we will do our best to
answer all of those questions when we talk to you next month. So that’s all I have
to say for now. Stay tuned. And Kate, do you
want to lose up?>>Katherine Zwaard: Okay. Thanks Lauren. I’d like to thank Judith and
Angela, too, for planning this and for doing all of the actual
work to make this possible. And thank you all
for coming today. Thanks, Mark, for
the introductions. I do want to note that many
people told me they had to leave at 3. What time is it? At 2 today. So if you notice empty seats
it’s not because people stormed. It’s just because they
had other meetings. So don’t panic. But I think we’ve
got, like, 10 minutes. So if there are comments or
questions or things you want to talk about, now would
be a great time to do that. Oh, and also there are
people in the back, hand them your worksheets. Do that. Yeah. Yeah. Any questions or
comments, or concerns, requests? Song titles that you — Ideas? Things that we should
be thinking about? Ways you would like us to get
to know you and your interests and needs and — Let me think. What else? What else? Yes.>>Hi, first of all, thank
you so much for putting on this wonderful presentation. A lot of this is news to
me, even though I do work in a digital division. So it’s really wonderful to see
you out and engaging with us. I was just wondering in general,
this is one of my questions but my pen ran out of ink,
do you do any open demos to the LC staff of some
of this technology?>>Katherine Zwaard: Great. Thank you for the kind words. And the question was
do we do any open demos to LC staff for this technology. So I think Meghan
shared a little bit about our communications
work in the past. And we’ve been really
heads down in doing things. And now I think now that
we have a little bit of additional capacity, it’s
time for us to pick our heads up and think more strategically
and coherently, cohesively. Coherently? Both. Cohesively and coherently
about how we can engage with you all and,
sort of, you mentioned that even though you work
in a digital department, a lot of this was news to you. That’s not what we’d
like, right? We would like for you to
be, sort of, at the level of awareness that
you’d like to be. So I think one of things we’re
considering is open houses and things like that. But I think actually
what would be best is if you could give some
examples of things that you’d like to see. I mean, would you like to
see that, sort of, thing? Like, a regular check in or –>>Yeah. I’m looking to get
more involved on Listservs. And, granted, I’ve only been a
library employee since the end of July, so that
might also be why. But I think I’d be
really interested in the open house idea. I think that would be terrific. More of a come as you can,
especially with, I’m sure a lot of us have lots of
responsibility that we have to attend
to as well. But I like that you have
events like these networking us with what’s going on maybe in different departments
of the library. I noticed that there’s a
communications initiative in place where you engage on
behalf of all the departments that are working with
digital technology, what everybody’s accomplishing. So I’m definitely
going to look at ways that we can engage our projects
over in my division with you.>>Katherine Zwaard: Great. Thank you. Oh, I should mention, that one
pager, please share that widely. It contains all the information
about the directional plan and the strategic plan
and the FY20 plan. So please do take a look it. And share with anybody you
think might be interested. Yes, ma’am.>>Terry: First question, is
the one pager on confluence?>>Katherine Zwaard: It sure is.>>Terry: Awesome.>>Katherine Zwaard: Yeah.>>Terry: Okay. Have you –>>Katherine Zwaard: A
fantastic piece of technology, courtesy of our friends
in OCIL [phonetic].>>Terry: Have you done anything
with kids since they think of technology in a whole
different way than we do? Like, a workshop in the Young
Reader Center to, kind of, say, you know, what’s
your blue sky idea as opposed to all us old folks.>>Katherine Zwaard:
I think that’s — So Terry asks have
we engaged kids? Because they think of technology
differently than we do. And I think that’s such a
super important question. A couple of years ago I read a
WIRED explainer about Snapchat. Which is it used
to be a magazine for people who knew things. And that explained — A
toy for children, right? And I’ve been, like,
checking out Tik Tok. I don’t know, how many of you
have seen, have been on Tik Tok? It’s so weird. And it definitely doesn’t fit
with my, like, old person reign. And so it will continue
to happen that there will be platforms and
places that people that we want to engage with crop up that
we are not even aware of. And so we’ve done some things
with the Young Reader Center. We we’ve been engaged in the
past with the team board. You know, I continue to
play on ridiculous apps at night while my husband
tries to tell me about his day. So I think that’s a
really good point.>>Was there a mouse? Okay. Is that it? Laura looks like she
wants to say something. You do. Yeah. Yeah. I can tell.>>Laura: It was
just striking me. I found it all so interesting
all the things you were talking about. And trying to think of ways that
the thinking can be brought back in to so the processes
that people go through in planning
these projects. If there was some way of making
a brainstorming sessions open to people to, kind of, so we
could be privy to how the, things that people
are thinking about. It also struck me recently there
a lot, the questions that come in about digital scholarship. And all those Twitter questions. Which are, you know,
not dirty laundry. But there’s a whole
database of them. And I was thinking, god, can we
just use them to teach selves, you know, what people
are looking for. Also, if there could be some
information shared in the kinds of questions that
come in like that. What do people want to do? Because I feel like
I don’t know. I’d love to know more.>>Katherine Zwaard: Yeah.>>Laura: And understand
the thinking. And the language that you all
use that I don’t, you know? Doesn’t come easily
to my tongue.>>Katherine Zwaard: So I’ve
been instructed by Judith to repeat the question. But that one was,
sort of, complicated, so I’m not going to do it. But I think I’m hearing
what you’re saying. And I think there’s a a couple
of things that we could do here. And one is that, you know,
a while ago, in 2017, the library convened a Digit
Scholarship Working Group Report, which you know about. A Digital Scholarship Working
Group, which produced a report. And that report has
been circulated. I think we’re looking to figure
out what of that we can publish to the wider world
and, sort of — Because it creates a necessary
framework upon which some of this work that
we’re doing rests. And in part of that is
we did some research, the group did some research into what question point
questions were there about digital scholarships. So one of the things we wanted to analyze was what demand is
there that we’re not meeting. And I think that there
is, it’s easy the ways in which we’re meeting user
demand are very visible, because we’re doing it. And we get, you know,
we get user numbers. And we get research outcomes. But the things that we’re not
able to meet are invisible because it’s a, sort of, a no and it doesn’t
really go any further. So as part of that working group
report, we collected a bunch of those requirements and use
cases and documented them. And I think that if you are
personally interested in that, we would love to chat more. But I think that that
is a valuable tool. One of the things I’ve
heard from a bunch of people is the interest in the
model of British library labs. Which does a, like,
quarterly introduction to digital scholarship. And digital library
at British Library. And I think that,
you know, sort of, resourcing is a question how we
would actually pull that off. And who would do it. But I think, I know when
I was a new person here that would’ve been
super useful to me. So I think that’s worth
chatting about as well. Yes, Elaine.>>Elaine: So my question is as
you’re thinking, or you’ve been in The Digital Strategy,
kind of, doing this for the last year,
and what has your vision around operationalizing? So there’s a bunch of
stuff that is happening, that’s gonna be happening
with machine learning. From those findings, or even
from tools that are created from those, or even an outcome
of a tool, are there any, like, a vision for how you will
share those tools to the staff that could use those tools
within their own work?>>Katherine Zwaard:
So Elaine asks about how do we operationalize
the things that we’re working on. And I have a nuanced not very
satisfying answer for you. I think that Abby showed that
chart of inputs and outputs. And I think that it’s
important to note that a lot of the outputs of these
experiments are our own greater degree of understanding
of a solution set or a problem space and/or a
better fidelity in questions that we’re asking and
not actually tools. But sometimes tools will
be the outcome, right? Sometimes we will try a thing
and, you know, we’re working with a division on
something, and we try a tool. And it’s just perfect,
and we just want to implement that as is. I think that’s actually going
to be a very small percentage of the projects we work on. I think more likely it will be
things like the Melon Project that Lori talked about. Where we’ll do two years
of experimentation. And then we’ll have
a better sense. Management will have
a better sense. Staff will have a better
sense of how or if this fits into our broader work planning. When we come out with a new
tool that we want to put into production, then we go through the IT investment
process. So that gets prioritized and
resourced in the same way that any new technology
investment would be done. Does that answer your question? Thank you. It was a great question. I mean, all the questions
were great. You know, I don’t want
to say yours was the best because it was just as
good as all the other ones. Anybody else? Okay. Please get in touch. You have our email. We would love to chat. Thank you.

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