AI is transforming learning in two main ways: 1) it is changing the capabilities that L&D needs to focus on through automation and personalization of learning experiences, and 2) it is changing how L&D works by providing insights into learning data. Ruby's day as a L&D professional demonstrates how AI tools can be used to gain insights from data, automate tasks like developing chatbots, and personalize learning for employees. While AI brings opportunities, issues around complexity of learning and lack of a "buy button" mean it cannot fully replace human judgment in L&D.

1. How AI is
transforming
learning

2. Dr Robin Petterd
Founder of Sprout Labs, host of the Learning While
Working podcast and virtual conference

3. Sprout Labs builds digital learning platforms that enable you
and your team to author, deliver and measure high impact
digital learning ecosystems.

4. Design Deliver Measure
Glasshouse is a cloud
based learning content
management platform
An open flexible and
affordable learning
platforms
Learn - An open
enterprise learning
management system
Social - An open social
enterprise system
Yield is a machine learning
engine for your xAPI data.
We include a learning
record store with all our
enterprise instances of
Glasshouse and Totara

5. • The Learning While Working podcast
• The blog
• eBooks
• The recordings of past webinars
• A virtual conference
Other content from Sprout Labs

6. What is AI?
Software that tries to simulate the way humans think

7. 1) It’s changing the capabilities
L&D needs to focus on
2) It’s changing how L&D works
AI is affecting L&D in two
ways

8. The future is already here —
it's just not very evenly
distributed
William Gibson

9. The Fourth Industrial
Revolution
Feels like the earlier days of the World Wide Web

10. The Future of Jobs - 2018
World Economic Forum
Survey of 317 CHRO on trends between now 2018-2022

11. The pessimistic view
The number of people in the workforce is reduced and less
learning is needed
Learning is automated

12. The age of abundance
Peter Diamandis

13. 58 Million potential
increase

15. Why is AI having this effect?

16. The growth of machine
learning
Software can make decisions in controlled
predictable situations
learning = It finds patterns in past data
Routine work can automated or augmented

17. How does machine learning
(ML) work?

18. Training - cup
1

19. Training - cup 2
Data scientist tells the system which features are important

20. Training - we show it lots of
cups

21. The system makes a ‘model’ of the cup

22. Sees a new cup - compares it the model
This is 80% like the model

23. This is called supervised machine
learning

26. This is called unsupervised machine
learning

27. Machine learning -
Supervised
Machine learning
- Unsupervised
Neural networks and
decision trees
Natural language
processing
What is it? You tell the system
what the ‘goal’ is e.g.
a cup and it finds
patterns whose
features are like the
goal
Find patterns in
data
A complex connected
set of if/then bits of
logic
Often a model that is
built with a ML
system ends up
being a decision tree
A cluster of
techniques that
tries to understand
language
Examples Recommendation
engines and
personalisation
Predictions - e.g. is a
learner behind or at
risk?
Analytics Planning tools Chat bots
Topic analysis
Sentiment analysis
of social data
All approaches need training data - which is the link between
ML and big data
A crash course in AI - in one slide

28. Built a data set of
all factors and
different
scenarios and
which topics a
doctor needs to
focus on
An AI powered study App for Doctors
Trained a
‘decision tree’
Exam success is often about a complex set of factors e.g. age,
patient profile, gender e.g a young female doctor might be great at
mental health but not so strong in geriatrics.
Doctors are not good at self-assessing in topics they are weak in.
The exam covers over 100 topics in 5 areas.

29. Automation is not AI - AI makes
automation smart

32. The Fourth Industrial
Revolution focuses us on what
it means to be human
Humans create
Humans collaborate - we are
social and emotional
Humans change

33. ‘Only 53% of CHROs surveyed are reasonably or
highly confident regarding the adequacy of their
organization’s future workforce strategy to
prepare for these shifts.’

34. Shift in your workforce
Reduce numbers Grow people
Reduce numbers in some areas
Recruit more people in the areas of need
Grow people into the new job roles. e.g.
a bank teller becomes data analyst
Skills shortage in the areas that everyone
needs to recruit in
2/3 of CHRO said this is what they plan to
do

35. What does this mean for L&D?
It’s an opportunity to grow learning
We need to become future focused
There are new skills that you need ‘bring’ into
organisation - quickly
We need to be agents of change
Learning while working is critical

36. Learning While Working
podcast series on
AI & L&D
There is a free eBook of transcripts to go along with this series. It’s
in the resources section of www.sproutlabs.com.au or send me an
email message - robin@sproutlabs.com.au

37. Performing GrowingOnboarding
Predictions
Personalisation
Recommendations
Chatbots
Who is struggling
Who is not learning
Which learning
experiences are
working
Answers
common
questions
Learning
experiences
allocated based
on KPI
Suggests learning
experiences
Who is motivated
to learn
Suggests learning
experiences
Guides the
experience
Just-in-time
performance
support
Guides learning
and reflection
Changes to help
with what they
might be
struggling with
Some of the current ways AI/ML is being used in L&D
Learning experience
L&D - gaining insights

38. 9:00 am Checks her dashboards
● Sees that Sam is struggling in the orientation
compared to others
● One of the discussion topics in the current
course in Curatr is not working
● Someone has posted a video on Yammer that
seems valuable
9:15 am Drilling into why Sam is struggling
9:30 am Updates the orientation chat bot
11:00 am Works with an SME expanding the chatbot to support
a new platform
1:00 pm Looks at what Filter Magpie has suggested to her as
learning for today
2:00pm Works on breaking an existing course into
microlearning so that Zoomi can personalise the
experience
3:00pm Works with Quillon on some knowledge questions
4:00pm Takes a learning break with her chat bot

39. What is Ruby not doing?
Figuring out what learning is right for employees
The personalisation and recommendations
systems are doing that
She is feeding the learning experiences into the
‘system’

40. It’s so hard to really understand what is happening in
our social learning programs. Curatr gives me a great
simple dashboard.
Podcast: Automating learning and measuring social learning with Ben Betts

41. HT2
Semantic
analysis
xAPI
xAPI
A natural language model
that has been trained to
find different types of
contributions
Understanding social data

42. One of the discussion topics isn’t getting higher order
complex responses. I’m going revise that and share the
video that is getting traction with the rest of
organisation.

43. Our retail orientation program take 3 months to
complete and sometime new employees start to
struggle.
It looks like Sam is struggling.
Rich set of powerful tools that
works with your existing
learning technologies
Recommendation and
predictions based on xAPI data
Podcast: The potential of AI in L&D with Christopher Brinton

44. Is the person’s past
behaviour similar to the
model?
What might they do in the
future?

45. Why doesn’t AI work in learning?
There is no ‘Buy now’ button - it is not simple
Critical nature of learning - recommending the
wrong course to a university student can be costly
Complexity of learning - outside factors
Healthcare has the same issues
Podcast: Learning analytics and machine learning in higher education with Mike Sharkey

46. Chatbots give our people just in time information on
the Intranet and CRM but we also use SMS. The
platform we are using is Mobile Coach
Podcast: Chatbots and L&D, with Vincent Han, AI and the modern learner, with Paul Healy, Performance support and
chatbots with Jamie Good

47. Our Intranet bot searches all the intranet data and our
learning content.
Podcast: AI and the modern learner, with Paul Healy
Otto from Learning Pool

48. Now it’s time for some of my own learning, I’m going to
check what Magpie has suggested.
Recommendation engines and learning are a natural
fit.
Podcast: Recommendation engines for learning, with Marc Zao-Sanders
A free service that is focused on
L&D content
A chat based recommendation
system for learning - this a great
way to get started

50. We don’t need a ‘Netflix’ of learning
Netflix is designed for passive engagement not
active performance
Netflix’s interface and system is optimised to
promote their content first
Podcast: Recommendation engines for learning, with Marc Zao-Sanders

51. I’m working on splitting out courses into small pieces of
microlearning. Zoomi works with our existing platforms
to personalise learning and gives me great insights into
what learners are doing.
There are other adaptive personalisation systems such
as Axonify.
Podcast: The potential of AI in L&D with Christopher Brinton

52. There are some knowledge questions I need to write.
I’m using Quillon from Harbinger. Quillon goes through
text and figures out short answer questions and simple
knowledge based questions.

53. Finally I’m going spend the last part of my day having a
learning conversation with Coach M from Lever
Learning.
Podcast: Using chatbots to increase learning transfer with Emma Weber

54. Turning Learning into Action
Free online action planning tool
http://turninglearningintoaction.com/
Podcast: Using chatbots to increase learning transfer with Emma Weber

55. Changes
Automation - personalisation, recommendations,
chatbots
Gaining new insights from data - predictions,
sentiment analysis

56. Delivery Workplace KPIDesign
Predictions about
who might
struggle
Personalisation based
what will increase KPIs
Recommendations
based on KPI
Brings in the context,
content, the learners
Makes suggestions based
on what has worked in
the past to improve KPIs
Automation and augmentation of learning design
Data driven learning design
This is happening
This is not happening yet

57. getglasshouse.com.au
If you want to talk about a more data driven approach to learning please just
reply to any email messages from Sprout Labs to start a conversation.
Dr Robin Petterd
M: +61 419 101 928
E: robin@sproutlabs.com.au