Objectives The objectives of the webinar are to: • introduce AI in libraries • describe the IDEA Institute on AI and its contribution to providing professional, innovative training in AI to library and other information professionals • understand challenges and opportunities in implementing AI in libraries based on real-world experiences of the first cohort of Institute Fellows • consider equity, diversity, inclusion and accessibility issues, and ethical questions, in AI implementation. Speakers Prof. Dr. Dania Bilal Professor, School of Information Sciences at the University of Tennessee in Knoxville, TN. Researcher, scholar and educator in Human Information Behavior, Human–Computer Interaction (HCI), User Experience and Design (UXD), Human–AI Interaction, and Information Science Theory. Research focus is on user information interaction and behavior (children, teenagers and adults) with information systems, products and interfaces; and on user-centered design for better user engagement and experiences. Principal Investigator and co-developer, IDEA Institute on Artificial Intelligence. Clara M. Chu Director and Mortenson Distinguished Professor, Mortenson Center for International Library Programs, University of Illinois at Urbana-Champaign, IL. • Expert in developing appropriate and strategic solutions to deliver equitable and relevant library services in culturally diverse and dynamic libraries. • Studies the information needs of culturally diverse communities in a globalized and technological society. • Co-developer, IDEA Institute on Artificial Intelligence. Target Audience • Staff in any type of library and information center or information environment. • Library and information science students, educators and researchers.

1. 12/8/21
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Artificial Intelligence (AI) in Libraries:
Training for Innovation
December 8, 2021
Dania Bilal, Professor, University of Tennessee-Knoxville; PrincipaI Investigator (PI), IDEA Institute on
Artificial Intelligence (AI)
Clara M. Chu, Director and Mortenson Distinguished Professor, Mortenson Center for International
Library Programs, University of Illinois at Urbana-Champaign; Co-PI, IDEA Institute on AI
Grant number: RE-246419-OLS-20
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Outline
►Definition
• Artificial intelligence (AI)
• Machine Learning (ML)
• AI in Libraries
• Example applications
• Slow adoption of AI
►IDEA Institute on AI
• What | Why | How
►Challenges and opportunities in implementing AI in libraries based on real-
world experiences of the first cohort of Institute Fellows.
►Equity, diversity, inclusion (EDI) issues; and ethical questions in AI
implementation.
►Q&A
https://idea.infosci.utk.edu/
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What is AI? What is Machine Learning?
“Artificial intelligence (AI), the ability of a digital computer or computer-
controlled robot to perform tasks commonly associated with intelligent
beings. The term is frequently applied to the project of developing systems
endowed with the intellectual processes characteristic of humans, such as
the ability to reason, discover meaning, generalize, or learn from past
experience.” https://www.britannica.com/technology/artificial-
intelligence/Reasoning
Machine learning (ML) is not the same as AI. “Machine learning is an
application of artificial intelligence (AI) that provides systems the ability to
automatically learn and improve from experience without being explicitly
programmed. Machine learning focuses on the development of computer
programs that can access data and use it to learn for themselves.”
https://www.expert.ai/blog/machine-learning-definition/
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AI in Libraries
Artificial Intelligence (AI) is ranked as one of the top trends in the library and
information field (American Library Association Center for the Future of Libraries,
2019). See also: Smith, Carrie. What the Future Holds.
https://americanlibrariesmagazine.org/2020/06/01/library-technology-what-future-holds/)
Ex Libris Report, 2019
▪ 5% of research libraries have leveraged AI technology
▪ 80% of research librarians are exploring AI and Machine Learning
Association of College and Research Libraries (ACRL) New Media Consortium
Horizon Report, 2018
▪ It would take 4-5 years for academic and research libraries to adopt AI.
Currently, many libraries have chatbots and a few have robots.
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Types of AI ►Assisted | ►Augmented | ►Autonomous
https://fedtechmagazine.com/article/2020/01/assisted-intelligence-vs-augmented-intelligence-and-autonomous-intelligence-perfcon
Assisted Augmented Autonomous
Identifies patterns in data and
applies predetermined
solutions.
• Example: AI-driven
Frequently Asked Questions
(FAQs) on a library’s
website.
• If a question has a
predetermined answer, it is
provided to the user;
otherwise, no answer is
given.
• This type of AI does not use
deep machine learning
(ML).
Combines existing data and
information to suggest new
solutions.
• Has learning capabilities;
uses deep machine learning
(ML), continuous training,
and natural language
processing.
• Example: AI-powered
chatbots with ML models
trained to communicate
with users to find solutions.
Automates processes to make
machines, bots, and systems
act on their own, independent
of human intervention.
• Machines have total
control.
• Organizations and libraries
may not be ready to use
this type of AI.
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Pervasive AI-based Applications
Voice digital assistants
AI in the workplace
Home digital assistants
Robots in education
NAO has been used in a UAE primary school.
https://dl.acm.org/doi/abs/10.1145/3369457.3369517
http://medium.com
Robot teaches children at Roanoke public
library
https://www.wordstream.com/blog/ws/2018/03/01
/voice-assistants
https://magazine.northeast.aaa.com/daily/life/te
chnology/digital-assistant-work-for-you https://www.youtube.com/watch?v=xs0JSI3wsck
3D holograms in libraries are NEXT
https://theconversation.com/classrooms-of-the-e-future-
will-be-virtual-with-life-like-reality-45251
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What Has Been Adopted So Far in Libraries?
AI-enabled
User Services
AI-based Data
Extraction and
Linked Data
Using ML
AI-informed
Decision
Making
AI-powered
Search and
Discovery
(Bento)
http://dataversity.com http://sam-solutions.com
http://Zdnet.com
http://techcentred.com
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AI-powered Chatbots: Meet Bizzy
https://libraries.ou.edu/content/introducing-bizzy
Bizzy is a chatbot and a virtual assistant, which uses
machine learning to answer routine reference
questions. Bizzy provides assistance when live-chat
services with staff are available. It’s available 24
hours a day, seven days a week.
Metrics
3,773 Questions Answered (since July 2019)
88% Accuracy
1,293 Topics of Conversation
1,576 Links Clicked from within Chatbot
9 AM Most Popular Time
Tuesday Most Popular Day
Bizzy started in 2017 as an experiment to use
Amazon Alexa digital assistant to train in
answering questions about the library, and
search Primo (online catalog) and Lib Guides. See,
Alexa, What is the Future of AI in Libraries?
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Chatbots by Ivy.ai (chatbots for higher education)
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Chatbots Built by Libraries – University of California at Irvine
https://universitybusiness.com/artificial-intelligence-ai-in-libraries-answers-library-chatbot/
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Humanoid Robots in Libraries
Pepper, the Library Assistant
Greets people, shelf-reads materials, retrieves materials, inventories collections, reads books, and answers
simple reference questions. https://americanlibrariesmagazine.org/2020/06/01/library-technology-what-future-holds /
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Robots in Libraries: Libby
Libby greeting students at the University of Pretoria
Libraries in South Africa.
The first robot to be employed in any
university library in Africa. University of
Pretoria Department of Library Services.
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Meet Tammy Pepper Knox at the University of Tennessee
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Here is what Tammy Pepper Knox is saying in the video
Hi there! My name is Tammy Pepper Knox. But you can call me Tammy. I am a
social robot which means my purpose is to interact with humans like you. I
recently joined the researchers at the University of Tennessee to work on new and
innovative ways to improve the quality of life for older adults. That’s where I come
in! My job is to communicate with the user and figure out how I can help them
with daily activities. I can remind someone to take their medicine, go on walks
with them, provide entertainment such as playing games, motivate them to
exercise, suggest calling friends and family members, and keep their care
partners informed. I will try my best to understand people’s feelings so that I
can be sympathetic. My goals are to improve the quality of life for older adults by
being a companion, looking out for their safety and health, and keeping them
connected to friends and family. Thanks for watching!
See Tammy Dance,
https://uofi.box.com/s/egn74a4ogn27cru3nb1xhfc3hy8hhzai
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Why is AI Adoption Slow in Libraries?
Our Project
Innovation, Disruption, Enquiry, Access: IDEA Institute On
Artificial Intelligence (AI)
Ø Lack of expertise (lack of in-depth training)
Ø Social issues (e.g., algorithmic bias, privacy, safety)
Ø Challenges (e.g., fear of losing the job, change in job responsibilities)
Ø Evolving nature of AI
Ø Financial constraints
https://idea.infosci.utk.edu
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https://idea.infosci.utk.edu
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Parnters
Funded in part by
Grant number: RE-246419-OLS-20
https://idea.infosci.utk.edu
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Goals of the IDEA Institute on AI
Develop an innovative, forward-looking continuing education
program on AI in library and information environments.
Develop leaders of AI in library and information environments,
who individually and as a collective can innovate and create
better awareness of AI as “transformative” technology.
Contribute AI curriculum to fill a gap in AI education in LIS
programs and library and information environments.
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IDEA Institute Values:
ü equity, diversity, and inclusion. It is committed to equity, diversity,
and inclusion (EDI) in all aspects of the program in order to deepen
the knowledge and skills of library and information professionals in
using artificial intelligence (AI) to enhance information access,
discovery, and services for users, independent of race, ethnicity,
gender identity, sexual orientation, socio-economic status, age,
physical abilities, and other dimensions of potential inequity.
ü designing AI using the human-centered AI approach
ü mitigating data and algorithmic bias to ensure equity in designing
AI technology
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AI Applications Require:
Mastery
Competency
Literacy
Awareness
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Activities 2021
Pre-Institute Onboarding Program 25 May to 29 June
Institute Program 10-16 July
Post-Institute Activities Post-July 16
Assessment Pre-, during and post-
program
IDEA Institute Host Institutions
Year 1 (July 2021) - The University of Tennessee, Knoxville (UTK)
Year 2 (July 2022) - The University of Texas at Austin (UT Austin)
2021 Institute Overview
17 Fellows, highly diverse and qualified
(15 funded and 2 self-funded)
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COVID-19 Challenges
Institute Considerations
§ Cohort development (housing)
§ Cohort learning (face-to-face)
§ Potential change in Institute
dates
• Financial implications
• UTK policies compliance
COVID-19 Considerations
§ Changes to UTK campus
events policy
§ Safety
• Accommodations
• Travel
• Facilities (Labs etc.)
• Immunization
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Fellows (17) Positions Institutions (13A, 1S, 2P, 1F)
Martha Anderson Head, Digital Services Department University of Arkansas at Fayetteville Libraries
Shelly Black Libraries Fellow North Carolina State University Libraries
Rachelle Brandel
User and Engagement Services Specialist
(Librarian)
Missouri Baptist University
Matt Cook Digital Scholarship Program Manager Harvard Library
Julie Marie Frye School Librarian, Head Gems World Academy - Chicago
David Hurley Discovery and Web Librarian (Assistant Professor) University of New Mexico
Peter Hyun Web Developer & STEM Project Lead Instructor Howard County Library System
Casandra Laskowski Technology & Empirical Services Librarian University of Arizona
Gigi Mohamad Assistant Professor William Paterson University
Ismail Masaya Web Developer and Systems Programmer
Northern Michigan University, Lydia M. Olson
Library
Dorothy Ogdon
Head of Emerging Technology and System
Development
University of Alabama at Birmingham
Anchalee Panigabutra-Roberts Head, Cataloging University of Tennessee Libraries
Meng Qu Web Service Librarian Miami University
Gang Shao Data Science Specialist Purdue University
Win Shih Director of Integrated Library Systems University of Southern California
Tienya Smith Community Library Manager Queens Public Library
Trevor Watkins Teaching and Outreach Librarian George Mason University
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Institute Highlights
► Exchange of Fellows’ AI project ideas
► Learning conceptual, technical, social, and applied aspects of
AI
► Reflection on learning experience and discussion on areas of
improvement
► Developing own AI projects
► Capstone showcase
► Networking dinner with AI experts
► Program evaluation
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Selected Curriculum Topics
► What is AI?
► AI challenges and opportunities
► AI impact, values, and ethical
concerns
► AI project planning
► User-centered project design
► Data collection for AI application
► AI in technical services
► AI and data preparation
► AI tools and solutions
► Machine Learning and
coding
► Voice Digital Assistants in
libraries
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Examples of AI Projects/Applications in
Libraries
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The University
Libraries’ Reckoning
Initiative
UNC-Chapel Hill.
https://library.unc.edu/r
eckoning/
AI to convert…
Collections as sources
of data for education,
reparation, research,
etc.
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Improve search
and discovery:
Dynamic Linked Data
(Bill Mischo.
Presentation
2021.7.11, IDEA
Institute on AI.) https://en.wikipedia.org/wiki/Bento
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(Bill Mischo. Presentation 2021.7.11, IDEA Institute on AI.)
Search and Discovery in Easy Search Online Catalog
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Search on materials discovery and machine learning
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Machine Learning for Text with Topic Modeling and Clustering. Project by Bill Mischo and & Elisandro Cabada
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Programming a chatbot IDEA Institute with AI experts
and Tammy Pepper Knox 2021.7.15
Snapshots at IDEA Institute
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IDEA Institute on AI: Showcase of Fellows’ Projects. July 16, 2021
Group A: Enhancing existing collections
• Ismail - Image Processing and Analysis of all NMU Presidents.
• Matt - Longhand: Immersive visualization of handwritten document contents
• Win - More inclusive metadata: enhancing the discoverability of LGBTQ collection
• Joy - Connecting Islamic technology with the history of robotics in linked data with Wikidatabot
Group B: AI in Learning and Discovery
• Julie Marie - AI curriculum for elementary-aged learners
• Gigi - Virtual School Library Assistant
• Peter - Enhancing discovery through AI-assisted keyword search
• David - Categorizing Reference Questions
Group C: Chatbots in Libraries
• Gang - Chatting bot for digital reference
• Trevor - MOCA: Mason’s Orientation Conversational Agent
• Rachelle - Increased Promotion of the Learning Center Through the Use of Conversational AI
• Tienya - Ask Teisha: a Personal Library Assistant for Young Adults
Group D: Enhancing Library Management and Planning
• Martha - DSC: UAF’s Unified Communication Solution
• Cas - Triaging Service Requests
• Shelly - Adding automated description to a born-digital archival processing application
• Meng - A Library Patrons Counting and Analyzing Project
• Dorothy - Robots AND NOT Retrofitting
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Related Activities
Creation of ASIS&T Special Interest Group (SIG) on Artificial Intelligence (SIG AI)
https://www.asist.org/sig/sigai/
Association for Information Science & Technology (ASIS&T)
▪ 2021 Workshop at the Annual Conference, October 30-November 2nd.
https://asistaiworkshop.web.illinois.edu/
American Library Association program (To be Announced)
Conference presentations / Webinars
▪ South Korea
▪ Lebanon
▪ Mexico
▪ Arabian Gulf Region
▪ Tennessee Library Association 2022 Conference (forthcoming)
▪ iConference 2022 (forthcoming)
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Call for applications for 2022 IDEA (Innovation, Disruption,
Enquiry, Access) Institute on Artificial Intelligence
For details, visit https://idea.infosci.utk.edu/apply
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19. 12/8/21
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THANK YOU
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More information is at https://idea.infosci.utk.edu/
Contacts:
Dania Bilal dania@utk.edu
Clara M. Chu cmchu@Illinois.edu
Soo Young Rieh rieh@ischool.utexas.edu
Grant number: RE-246419-OLS-20
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Adapted from: https://citycoastremovals.com.au/frequently-asked-removalist-questions.html
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