Artificial Intelligence in Library and Educational Settings Concerns and Opportunities Introduction In this webinar, attendees will learn about Artificial Intelligence (AI), become familiar with its basic functionality, and examine specific examples of its use in library and educational settings. The presenter will also identify ways in which AI may be used in the future. Objectives The webinar will: describe artificial intelligence identify ways AI can be used in library and educational settings consider the ethics of using AI in educational settings. Moderator Dr. Lauren Hays Dr. Hays is Assistant Professor of Educational Technology at the University of Central Missouri, Warrensburg, Missouri, USA. Previously, she was an Instructional and Research Librarian at a private liberal arts university. Target Audience Academic librarians Public librarians

2. About Me
• Assistant Professor of Educational Technology at the
University of Central Missouri.
• Previously, an Instructional and Research Librarian at
a small liberal arts college.

3. Outcomes
• Describe artificial intelligence
• Identify ways AI can be used in
library and educational settings
• Consider the ethics of using AI in
educational settings

4. What is
Artificial
Intelligence?
• AI is a computer system that is
able to perform tasks that
normally require human
intelligence such as visual
perception, speech recognition,
decision making, and
understanding human language

5. AI
Examples
• Manufacturing robots
• Self-driving cars
• Smart assistants
• Proactive healthcare management
• Disease mapping
• Automated financial investing
• Virtual travel booking agent
• Social media monitoring
• Inter-team chat tool
• Conversational marketing bot
• Natural Language Processing (NLP) tools
• -List from https://builtin.com/artificial-
intelligence/examples-ai-in-industry

6. MixLab
• https://mixlab.withgoogle.c
om/
• MixLab is a tool created by
Google that lets you mix
music by telling the
computer what instruments
to add, what beat to use,
etc.

7. Speechnotes
• https://speechnotes.co/
• Speechnotes allows you to
enable voice-typing on any
site.

8. Teachable
Machine
• https://teachablemachine.
withgoogle.com/
• Teachable machine is a way
to train your computer to
recognize images and
sounds.

9. AI
Experiments
• https://experiments.withgo
ogle.com/collection/ai
• "AI Experiments is a
showcase for simple
experiments that make it
easier for anyone to start
exploring machine learning,
through pictures, drawings,
language, music, and
more."

10. Scratch
Bot
• https://en.scratch-
wiki.info/wiki/Creating_a_C
hat_Bot
• Scratch bot is a tool you
can use to create a chat
bot.

11. AR
Experiments
• https://experiments.withgo
ogle.com/collection/ar
• a Google tool that lets
developers create new AR
experiences

12. Cognimates
• http://cognimates.me/get-
started/
• a tool for building games,
programming robots, and
training AI models

13. Other
examples you
have seen?

14. Using AI in
Libraries

15. IFLA
Statement
on AI in
Libraries
• “The adoption of artificial intelligence and machine
learning systems in private and public spheres is
rapidly growing. How can these developments
impact both everyday practices and the broader
social mission of libraries? IFLA's new statement
sets out some key principles. The rapid pace of AI
development and adoption raises crucial questions
about intellectual freedom, equity and privacy,
automation, the evolution of necessary digital
literacy skills, relevant Intellectual Property policy
frameworks, and more. The new IFLA FAIFE
statement aims to outline key considerations for
the use of AI and ML technologies in the library
sector, and suggest the roles which libraries
should strive to take on in a society with growing
AI integration.” -Abstract

16. AI and
Libraries
• AI in the Library: integrating AI
and machine learning
technologies into everyday work
• Libraries can educate users about
AI, and help them thrive in a
society which uses AI more
extensively
• Libraries can support high-quality,
ethical AI research
-From IFLA

17. Staying up-
to-date

18. Libraries
should:
• Help their patrons develop digital literacies that
include an understanding of how AI and
algorithms work, and corresponding privacy and
ethics questions.
• Continue to focus their efforts to enable lifelong
learning and, where possible, provide services
for the unemployed.
• Ensure that any use of AI technologies in
libraries should be subject to clear ethical
standards and safeguard the rights of their users.
• Procure technologies that adhere to legal and
ethical privacy and accessibility requirements.
-From IFLA

19. Library
trainers and
associations
should:
• Support library professionals to understand the impact
of AI as well as its intersections with privacy and ethical
principles. Library training providers should ensure that
librarians are able to develop relevant digital skills and
competencies.
• Advocate for libraries to play a bigger role in changing
education systems as they adapt to the labour market
changes which AI might bring.
• Engage with AI researchers and developers to create
applications for library use, which meet ethical and
privacy standards and respond specifically to the needs
of libraries and library patrons.
• Act as forums for exchanging best practices on ethical
use of AI technologies in libraries.
-From IFLA

20. Everyday
Examples
of AI in
Libraries
• Chatbots
• Database search
recommendations
• Content indexing
• Relevant articles
• Impact factors

21. Other
examples you
have seen?

22. Using AI in
Education

23. Everyday
Examples
of AI in
Education
• Personalized learning
• AI Tutors
• Task automation for instructors
• Increased access
• Learning analytics

24. Other
examples you
have seen?

25. Example
of AI in
Education
• ISTE Resources:
https://www.iste.org/areas-of-
focus/AI-in-education

26. The
Future of
AI in
Libraries
and
Education
• Increased automation
• Use in all sectors
• Increase in use of data
• Removal of some human elements

27. AI and
Ethics
• Discrimination
• Bias
• Privacy
• Removing the human element

28. Ethics of
AI in
Education
• Informed consent
• Can include minors
• Importance of human connections
in learning

29. Use an Ethical Framework
1. Identify stakeholders.
2. Identify values: ethical and nonethical.
3. Ethical values trump nonethical values.
4. If two ethical values conflict, the one that produce the
greatest good for the greatest number wins. (Maner, 2002,
p. 349)

30. Example Scenario
A group of middle students are working on a coding project. Their task is to design a technology
that will help others. The group decides to write a code that will trigger a camera to record
video of children playing on the playground so they can identify when a child has been bullied.
The teacher wants to encourage students to think more critically about this idea.

31. Ethical Procedure Guiding Question
Identify stakeholders Who is involved? Who will be affected? Who will be
helped? Who will be hurt?
Identify values What is the value of this project? What are the
reasons we should create this project? What are the
reasons we should not create this project? What will
happen if…(e.g. a student is embarrassed about what
is seen on the video? The camera records things not
related to bullying? Someone is accused incorrectly of
being bullied? What if someone is bullied and the
camera doesn’t catch it?)
Ethical values trump non-ethical values Do any of these concerns fall within one of the core
human values? (e.g. life, health, happiness, security,
resources, opportunities, knowledge, privacy)
If two ethical values conflict, the one that produces
the greatest good for the greatest number wins
Is there a way to modify this system to produce more
good for more people?

32. Resources
• Center for Humane Technology:
https://www.humanetech.com/
• https://ethicalairesources.com/

33. Questions?

34. References
• Davis, M. (2006). Integrating ethics into technical courses: Micro-insertion. Science and
Engineering Ethics, 12(4), 717-730. https://doi.org/10.1007/s11948-006-0066-z
• Kammer, J., & Hays, L. (2021). Coding in School Libraries: Considering an
Ethical Approach. Education Libraries, 44.
• Kert, S. B., Uz, C., & Gecu, Z. (2012). Scenarios for computer ethics
education. Procedia-Social and Behavioral Sciences, 46, 2706-2710.
• Maner, W. (2002). Heuristic methods for computer ethics. Metaphilosophy, 33(3), 339–
365. https://doi.org/10.1111/1467-9973.00231