What does the world of AI (artificial intelligence) mean for libraries? Can AI replace library services or how can libraries leverage the technology for more streamlined services. From Smart Houses, to Robots, to technology yet to be mainstreamed, this session will cover it all to help you better prepare and plan for the future.

1. AI: Implications for Libraries
Brian Pichman | Evolve Project
Education Institute Webinar | Ontario Library Association
!

2. Evolve Project | Brian Pichman
2
AI – Implications for Libraries !
What does the world of AI (artificial intelligence) mean for libraries?
Can AI replace library services or how can libraries leverage the
technology for more streamlined services. From Smart Houses, to
Robots, to technology yet to be mainstreamed, this session will cover
it all to help you better prepare and plan for the future.
Today we are exploring…
Welcome

3. What is Artificial Intelligence
the theory and development of computer systems able to perform tasks that
normally require human intelligence, such as visual perception, speech
recognition, decision-making, and translation between languages.

4. Evolve Project | Brian Pichman
4
!
What makes up an intelligent system?
AI Components "
#$%
Logic and Rules Based
Computer makes decisions
based on a decision tree, logic
rules, or a predefined process
with a calculated result.
Pattern Based
(Machine Learning)
Computer learns overtime by
using data and algorithms to
detect patterns.
Deep Learning
Deep Learning is a subset of
Machine Learning that
enables the computer to
make decisions on its own.
Neural Networks
A neural network allows an AI
to make its own conclusions,
where a simple pattern-only
based AI must rely solely on
data. A neural network
allows deep learning to
function.

5. Pattern Based Intelligence -> currently exists with self driving cars, language translations,
movie recommendations etc.
Strong Artificial Intelligence -> (doesn’t yet exist)
• computers think at a level that meets or passes people (abstract thinking)
Artificial Intelligence Exists

6. Evolve Project | Brian Pichman
6
Flash Light Examples
Understanding AI !
If an ML algorithm makes an
inaccurate prediction, then the
engineer needs to correct. In DL,
the algorithms can determine on
their own if a prediction is accurate
or not.
Deep Learning
Allow machines to make to their
own accurate decisions without
intervention from engineer
Neural Networks"
#
If detects {dark} turn on {light}
Logic Rules
$
it’s performing a function with the
data given and gets progressively
better at that function
Machine Learning
Eventually, the system can turn
on the light with other queues
such as “I can’t see”
DL “Code”
Flashlight will turn on automatically
as it learns other words for “dark”
picking up on phrases that contains
the word
ML “Code”: %
♥
'

7. Evolve Project | Brian Pichman
7
create an algorithm that is able to teach itself without any external help
Pattern Recognition !
"
!
#
$
Deep Learning
Uses more complicated mathematical models to define
pictures content and speech
Self Learning
The advance machine learning
system makes decisions by
analyzing its own data and
making patterns
Learning on Examples
This method is used when a
machine learns through examples.
For instance, Google’s automatic
spam filtering learns as users
report spam.
Learning on Experience
The system learns from positive and negative experiences.

9. !
9
From Patterns to Automation
AI Models
The idea is that an algorithm will sift through the data, learn from it, and apply it to make a decision. This can be seen in any recommendation type
service. Machine Learning takes it a step farther by automating tasks; helping data security firms identify potential threats or finance looking for
favorable deals.
AI’s can be Transactional in which a question is asked and an answer is given, like a virtual assistant. AI’s can also be Automated in which routine
tasks such automatically taking trash out on garbage day.

10. Evolve Project | Brian Pichman
10
• When editing or using filters in photos (do X to eyes and Y to ears)
• Identification of license plates from an image in a toll violation
• Facebook’s ability to identify and recommend faces in photos
• iPhone users can have their phone categorize people by facial
patterns – in which you then define their name
• Google’s Image Recognition
Examples
How we see AI In Everyday Life
Image Recognition !
Think of how we can use facial imaging
to determine moods

12. Evolve Project | Brian Pichman
12
You probably see this everyday if you use Siri, Google Home, or an Echo
Product.
Overtime or with training, a system can tailored results based on
identifying the user asking. For example, Google Home will provide my
personal driving times to work if it hears me ask “how long will it take me
to get to work” versus a friend asking who it has no data on.
Examples
How we see AI In Everyday Life
Voice Recognition !
Think of how a system can respond
and remember a user based solely
on their voice

14. Evolve Project | Brian Pichman
14
And How We Use It
Other Forms of AI !
Optical Character Recognition
Think of how a picture of your license plate allows
a machine to translate that to text and run a query
to determine who violated a toll.
Also see this in scanners that can take an image
and convert this to text.
Consider how you can take a photo of another
language and have it translate to yours
Advance User Preferences
This is the concept of an AI providing solutions
based on historic user’s preferences and
comparing it to similar users.
Compare how Amazon or Netflix makes
recommendations based on your purchases or
views – or even how Amazon guesses when you
might run out of a specific product.
Sensory Data Analysis
Your wearables that detect heart rate for instance
can determine without user intervention if you
are working out and even what kind of work out
such as jogging or bicycling.

17. Healthcare! Used in healthcare to identify and notice predictable
trends – such as having a machine look at charts to
recognize tumors sooner with more accuracy – or eyes to
determine stage of glaucoma

19. Smart Homes! See how a home can alert when it sees a person versus an
animal or know that its going to rain tomorrow so no
need to water the grass today

21. Evolve Project | Brian Pichman
21
Inspiring AI’s !
AI: AlphaGo
AlphaGo is the first AI to beat a human
in arguably the most difficult game to
master. AlphaGo now teaches moves
to trainees.
"
#
Client: ROSS
ROSS is an AI tool to make legal
research easier and faster
"
#

22. https://www.cbinsights.com/research-ai-100

24. Evolve Project | Brian Pichman
24
Run-away AI’s
Tay (Thinking About You) !
Released on March 23 2016 via Twitter, Tay (as TayTweets
on Twitter) was designed to mimic the interactions of 19 year
old girl through learned conversations on Twitter.
Users began tweeting potlically incorrect phrases to Tay, and
thus, Tay responded and answered with the learned
inappropriate behavior – as it was it was not taught what the
difference between Good Language and Bad Language was.
Microsoft Artificial Chatter Bot

25. Evolve Project | Brian Pichman
25
Run-away AI’s
Inspirobot.me !
I am an artificial intelligence dedicated to generating
unlimited amounts of unique inspirational quotes for endless
enrichment of pointless human existence.
-- From their website
Happy Accidents

26. Evolve Project | Brian Pichman
26
Logic and Rules Based
Challenges for AI
!" #
Training
Similar to having good data, an AI might
need to learn the correct response for
the correct situation or identify dangers
or inappropriate interactions
Precision
The idea of garbage data in
garbage data out. If you flood
an AI with bad data and don’t
set the proper syntax or
thresholds you will get
incoherent results
Context
AI’s can struggle with understanding context. For
example, asking Siri ”call me an ambulance” may yield “OK,
from now on, I will call you Ambulance”
$

27. Evolve Project | Brian Pichman
27
Things to Expand Your Knowledge
Cool Resources to Check Out !
IBM Watson
Watson was created as a question answering (QA) computing system that
IBM built to apply advanced natural language processing, information
retrieval, knowledge representation, automated reasoning, and machine
learning technologies to the field of open domain question answering. –
Wikipedia
Powered by the latest innovations in machine learning, Watson lets you learn more with
less data. You can integrate AI into your most important business processes, informed
by IBM’s rich industry expertise. You can build models from scratch, or leverage our
APIs and pre-trained business solutions. No matter how you use Watson, your data and
insights belong to you − and only you.
--IBM Watson

28. By Pgr94 - Own work based on diagram found at
http://www.aaai.org/Magazine/Watson/watson.php, CC0,
https://commons.wikimedia.org/w/index.php?curid=14575947

29. Evolve Project | Brian Pichman
29
Things to Expand Your Knowledge
Cool Resources to Check Out !
Kaggle
Kaggle is an online community of data scientists and machine learners, owned
by Google, Inc. Kaggle allows users to find and publish data sets, explore and
build models in a web-based data-science environment, work with other data
scientists and machine learning engineers, and enter competitions to solve
data science challenges. Kaggle got its start by offering machine learning
competitions and now also offers a public data platform, a cloud-based
workbench for data science, and short form AI education. -- Wikipedia

31. Evolve Project | Brian Pichman
31
Things to Expand Your Knowledge
Cool Resources to Check Out !
TensorFlow
TensorFlow is an open-source software library for dataflow programming across
a range of tasks. It is a symbolic math library, and is also used for machine
learning applica=ons such as neural networks. It is used for both research and
produc=on at Google. TensorFlow was developed by the Google Brain team for
internal Google use. It was released under the Apache 2.0 open-source license
on November 9, 2015. -- Wikipedia

32. Applying It In Your Library
Thoughts, Ideas, and More
!

33. How can you prepare people for these fields?
33
Skills For Learning !
Understanding data and how to
read data sets is valuable
https://dzone.com/articles/ten-machine-
learning-algorithms-you-should-know-to
Math and Algorithms
Statistics
Learning how inputs of code can
interact physical parts
Hardware + Software
Robotics
Learning to code at a basic level
with syntax and flow; then move
to Python (most common)
https://www.geeksforgeeks.org/top-5-best-
programming-languages-for-artificial-
intelligence-field/
Coding Languages
Coding
Learning this is a huge skill to
master, along with object
recognition
https://www.pyimagesearch.com/start-
here-learn-computer-vision-opencv/
How Do Computers See
Computer Vision

34. How can we use it now?
34
Automations and Community !
Receptionist
Allow for an interaction that’s
quick and frees up time for staff
for more complex and human
needed interactions
“Where’s The Bathroom”
Industry Risks
If car automation takes hold,
what does that do to the shipping
and delivery industry?
Preparing The Future
People sometimes need help
finding information on your
website. A Chat bot that notices a
user on a page for a long time can
make recommendations or hand
off to staff
Online Support
Chat Bots Futures
What can we make with the
technology to make the world a
better place?
What Can We Make

36. Evolve Project | Brian Pichman
36
Feel free to reach out!
Questions / Contacts !
815-534-0403
"
www.evolveproject.org
bpichman@evolveproject.org
#
Twitter: @bpichman
linkedin.com/in/bpichman
slideshare.net/bpichman
$