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TRUST and EXPLAINABILITY
OSWALD, an inside view
PARTENA CASE
TRAIN INTERFACE
BOT BRAIN
CONFUSION MATRIX
TEST CASES
STATISTICS
HUMAN TAKEOVER
”I want to go to Paris in two weeks”
CHATBOTS
OSWALD
Real quick!
Intent
+
Entities
+
Context
=
Response
I want to go to Paris in two weeksDestination:Paris Date:2020-02-27
intent: Plan Trip Context:
- name: John Doe
- Means: Flight
- Location: LA, CA
Ok John, here are some flights you might like…
CHATBOTS
OSWALD
In Oswald
Intent
+
Entities
+
Context
=
Response
CHATBOTS
OSWALD
In Oswald
Intent
+
Entities
+
Context
=
Response
CHATBOTS
OSWALD
In Oswald
Intent
+
Entities
+
Context
=
Response
PARTENA CASE
OSWALD
Disclaimer
Sorry no data on Partena in this presenation!
But we will show you the tools they have
available J
PARTENA CASE
OSWALD
Before
Call center with information in large CMS
system.
Customers with a question immediately end
up with the helpdesk
Helpdesk manually takes customers through
the flows defined in CMS
PARTENA CASE
OSWALD
Then
Right.
Let’s automate!
Synchronize CMS with Oswald!
Works! Gaining understanding of the user.
But little control, different medium, …
PARTENA CASE
OSWALD
Now
In control.
Clear flows, understand why the chatbot
behaves as it does.
Integrate with backend systems.
And adapt to the user.
TOOLSUITE
TRAIN INTERFACE
OSWALD
Try out and unanswered
Enter some text here and see how the bot
understands your input.
Also find input sent by your users that hasn’t
been handled as it should.
Filter by problem type, intent score, archive
status
View brain and takeover
Building Trust and Explainability into Chatbots: the Partena Ziekenfonds Business Case, presented by Karel Kremer, CTO of Oswald, at the Trustworthy and Ethical AI Conference on Feb 13th, 2020
BOT BRAIN
OSWALD
Have a look at how Oswald
THINKS!
What are the intent and the entities it
understood?
What was in context? How did the response it
gave change that?
Any tags in the session?
Which response did it give?
BOT BRAIN
OSWALD
BOT BRAIN
OSWALD
BOT BRAIN
OSWALD
BOT BRAIN
OSWALD
CONFUSION MATRIX
OSWALD
What confuses your bot?
Train your bot on 80% of training sentences
Use the other 20% as input and examine the
results.
This can be a measure for how well your bot
will perform on new input.
Which intents are too much alike, which
simply need more training sentences?
Building Trust and Explainability into Chatbots: the Partena Ziekenfonds Business Case, presented by Karel Kremer, CTO of Oswald, at the Trustworthy and Ethical AI Conference on Feb 13th, 2020
Building Trust and Explainability into Chatbots: the Partena Ziekenfonds Business Case, presented by Karel Kremer, CTO of Oswald, at the Trustworthy and Ethical AI Conference on Feb 13th, 2020
TEST CASES
OSWALD
Trust that your chatbot
handles changes
When retraining intents
When adding rules to scenarios
When modifying critical responses
Building Trust and Explainability into Chatbots: the Partena Ziekenfonds Business Case, presented by Karel Kremer, CTO of Oswald, at the Trustworthy and Ethical AI Conference on Feb 13th, 2020
STATISTICS
OSWALD
How do your users actually
use your chatbot?
What intents are used?
What scenarios?
What tags?
Load?
STATISTICS
OSWALD
HUMAN TAKEOVER
OSWALD
When your bot needs a
hand
View and filter conversations
Take over from the bot when things go wrong
How did the user get here?
HUMAN TAKEOVER
OSWALD
HYBRID CLOUD / ON PREM
OSWALD
TRUST
OSWALD
Make humans feel safe
from the scary robot…
Bot vs. Human
Ask consent
Anonymize your data
Send transcriptions
Forget Me
DEMO
OSWALD
Thank you
OSWALD

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