Getting Started With Using AI In Libraries (PLAN)

Getting Started with AI
Brian Pichman
Evolve Project
@Bpichman
Mastadon: https://libraryland.social

Evolve Project | Brian Pichman
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AI: The Good, The Bad, The Ugly
This session explores what artificial intelligence (AI) is and the
everyday use cases for AI. It’s an introductory look at how various
industries, including libraries, use AI for operational efficiencies,
enhanced services, and more.
Today we are exploring…
Welcome

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.

What is Machine Learning
Machine Learning is a subset of Artificial Intelligence that uses algorithms
and statistical models to allow a computer system to make decisions
around a specific task without explicit instructions; relying on patterns and
inference

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When talking about AI…
People will have one of two
reactions:

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“The Agenda”
Topics for Today
AI As A Tool
When introducing AI to the its
best to explain what it is…and
what it isn’t.
Impacts to Industries
How are we seeing AI Impact
different industries now?
Pulling it Together
How can we embrace AI and
move things forward?
Using AI
Many of us interact regularly
with some variant of Artificial
Intelligence.

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AI is becoming more available to the masses; being incorporated into
our smart phones, our connected homes, and simple robots we
already use today such as Roomba. With more accessible cloud-
computing, open source, and the making community, this field will
rapidly expand.
More Widely Available
Using AI
“The development of full artificial
intelligence could spell the end of the
human race….It would take off on its own,
and re-design itself at an ever increasing
rate. Humans, who are limited by slow
biological evolution, couldn't compete,
and would be superseded.”— Stephen
Hawking

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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.

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

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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”:

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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.

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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.

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• 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

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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

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Helpful – AI

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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.

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

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Good Read:
https://www.businessinsider.com/healthcare-artificial-intelligence-pitfalls-2019-3

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

Service Industries
AI has the potential to replace many minimum wage jobs

https://www.bbc.com/news/av/technology-43292047/burger-flipping-robot-begins-first-shift

Autonomous Driving
Autonomous driving Level 4 describes vehicles that can operate without human interaction in most, but not all, conditions and locations and will likely operate in geofenced areas.
Autonomous driving Level 5 labels vehicles operating autonomously in all situations and conditions, and controlling all tasks.

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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.
AI: ROSS
ROSS is an AI tool to make legal
research easier and faster

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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 pollitcally 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

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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

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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”

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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

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

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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

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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

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Books written by an AI
https://link.springer.com/book/10.1007/978-3-030-16800-1

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AI Games
AI Image or Not: http://www.whichfaceisreal.com/
https://experiments.withgoogle.com/collection/ai

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AI Content Creation Tools
Learn more about these in the other sessions today!

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Activity
https://affinelayer.com/pixsrv/

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AI for Your Library
AI can be used in a variety of different ways. During this session, we
will focus on how AI can be used within the library, including:
running an AI programming class, using AI to answer simple
questions, and utilizing AI to create posts, tweets, photos, and even
videos for our library. Leave this session with a variety of AI tools
you can start using in your library!
Today we are exploring…
Welcome

Applying AI
Thoughts, Ideas, and More

How can you prepare people for these fields?
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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

How can we onboard AI today?
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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

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https://youtu.be/emQqjrhV3Jo

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AI Games
AI Image or Not: http://www.whichfaceisreal.com/
https://experiments.withgoogle.com/collection/ai

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AI Content Creation Tools

Automatic Postings of Curated Content

https://instoo.com/
https://appsumo.com/products/marketplace-instoo/

AI Assistants for Content
AI Content Tools:
· https://rytr.me/
o Create stories, blogs, tweets from
a few key words generated by AI
· https://app.wordhero.co/home
o Create text for a variety of
different topics
· https://app.peppertype.ai/home
o Create text for a variety of
different topics
Video Creation
· https://pictory.ai/
o Create curated stock videos based
on your text
Audio Creation
· https://app.fliki.ai/
o Text to Speech with a variety of
voice overs
Art Creation:
· https://supermachine.art/
o Create AI Generated Art
· https://aiimages.ai
o Create Image Content

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“The Agenda”
Bringing It All Together
Impact On Staff
At some point, AI can very well
replace some functions and
roles of what we do. IE:
Receptionist/Simple Q & A
Improving AI
If building an AI solution, you
will want to be accurate with
the data you provide

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Making Your Job Better
Shift of Focus
AI can replace many of our tasks that we do to make them:
* More Efficient =
* More Accurate = As long as the data provided to the
AI is “good”, then the function will be more accurate.
*Tedious Work may be “outsourced” to the AI
Making The Work Day More Meaningful

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AI Struggles
Shift of Focus
AI may not have emotional intelligence or show
empathy…(yet).
AI makes a decision based on facts and may
not account for emotional variables.
To assume AI can’t replace a job role because it
doesn’t have emotional intelligence would be a
failure point to any organization.
Empathy / Emotional Intelligence

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Maslow

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Live Demos!

https://codepen.io/GeorgePark/pen/gKrVJe

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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

Getting Started With Using AI In Libraries (PLAN)

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