Not so long ago, we interacted with websites by clicking buttons, and with people by talking to them. Those lines, however, are becoming increasingly blurred, with real people guiding our website interactions and computers running phone, Twitter, and Facebook Messenger interactions. An increasing number of these interactions are voice, rather than text, ones. What does it all mean? Are websites obsolete, or is this a passing fad? Is chatbottery the new HMTL, only without the standardization? This session presents a practical introduction to how chatbots work, their advantages, their limitations, and where they should and should not be used.

1. Holly Cummins
@holly_cummins
with
Sock, the Socratic Helper

2. I’m from the IBM Cloud Garage.
(It’s not actually a Garage.)

3. I’m from the IBM Cloud Garage.
(It’s not actually a Garage.)
I’m from IBM’s London Chatbot Garage.

4. Can you
build me a
chatbot
please?
Lean startup,
innovation, test-
driven
development, pair
programming,
design thinking …
IBM Bluemix Garage London

5. It’s 2017.
Chatbots are everywhere.
Even in games.

6. There are currently more than 33,000
chatbots on Facebook Messenger alone.

7. It’s 2017.
There’s more natural language understanding.
There’s more automation of boring tasks

8. Why does everyone want chatbots?
They’re interesting and they solve
problems.

9. Not all chatbots do the same things.

11. Chit-chat bot Worker bot

12. Chit-chat bot Worker bot
Neither user nor
bot have a goal

13. Chit-chat bot Worker bot
Neither user nor
bot have a goal
Both user and
bot have goals

14. Chit-chat bot Worker bot
Neither user nor
bot have a goal
Both user and
bot have goals
I invented these terms!

15. The success metrics are different.
Turing Test Containment

17. Chatbots are not new.

18. ELIZA
1964
Person: Men are all the same.
ELIZA: IN WHAT WAY.
Person: They are always bugging us
about something or other.
ELIZA: CAN YOU THINK OF A SPECIFIC
EXAMPLE.
Person: Well, my boyfriend made me
come here.
ELIZA: YOUR BOYFRIEND MADE YOU COME
HERE.
Person: He says I'm depressed much
of the time.
ELIZA: I AM SORRY TO HEAR YOU ARE
DEPRESSED.
Person: It's true, I am unhappy.
ELIZA: DO YOU THINK COMING HERE WILL
HELP YOU NOT TO BE UNHAPPY.
Person: I need some help, that much
seems certain.

19. 2011: 5 minute Turing Test
Cleverbot Human

20. 2011: 5 minute Turing Test
63.3%
Cleverbot Human

21. 2011: 5 minute Turing Test
59.3%
63.3%
Cleverbot Human

22. 2011: 5 minute Turing Test
59.3%
63.3%
Cleverbot Human

23. Estragon: I am a human. You
are a computer.
Vladimir: No I am not.
Estragon: Yes you are, and
I'm a human being
Vladimir: But you said you
are a robot.
Estragon: No I didn't! YOU
said I was a robot.
Vladimir: But you are.
Estragon: I know you are but
what am I?
Vladimir: You are human.
Estragon: And you are a
robot.
Vladimir: But you just said
you were a robot.
Estragon: Na I asked if you
were a robot and you said
yes.
Vladimir: Nope. You are a
manipulative bunch of metal.

25. Is this interesting?
Yes, very.

27. Is this useful?
Err…

28. Worker bots are designed to be useful.

29. They are limited, but (usually) helpful.

32. Do you need a chatbot?

33. Do you need a chatbot?
Often, no.

34. Do you need a chatbot?
Often, no.

35. Unless … conversations are kind of
boring for the people doing them now.

36. Unless … users want to use pervasive
channels.

37. Unless … users need aggregated
information.

39. The chatbot fallacy:

40. The chatbot fallacy:
“If a bot can understand a user
speaking, it can have a conversation.”

41. The chatbot fallacy:
“If a bot can understand a user
speaking, it can have a conversation.”

42. The chatbot fallacy:
“If a bot can understand a user
speaking, it can have a conversation.”
Voice is a well-solved problem.

43. The chatbot fallacy:
“If a bot can understand a user
speaking, it can have a conversation.”
Voice is a well-solved problem.
That doesn’t mean the rest of
conversation is.

44. Demo!

48. Watson
Speech to Text
Watson
Conversation
React.js
client
Bluemix
weather
service
WebSphere
Liberty
PDFs
Public Internet
IBM Bluemix

49. Did I mention
Open Liberty is
now open source?
Watson
Speech to Text
Watson
Conversation
React.js
client
Bluemix
weather
service
WebSphere
Liberty
PDFs
Public Internet
IBM Bluemix

50. This is what we’ve learned
building a lot of chatbots.

51. Explain limitations.
Give examples of
what can be asked.
I’m sorry, I’m not smart
enough to fix that yet.
You can ask me about
applying for a credit card
or changing your
address.

52. ? ? ?
Don’t be afraid to
say “I don’t know.”
Complex complex
my grandmother’s
octopus needs a
new sofa on
rollerskates?

53. ? ? ?
Don’t be afraid to
say “I don’t know.”
Complex complex
my grandmother’s
octopus needs a
new sofa on
rollerskates?

54. ? ? ?
Don’t be afraid to
say “I don’t know.”
Complex complex
my grandmother’s
octopus needs a
new sofa on
rollerskates?

55. Hand off to a human

56. Users are lazy.

57. Don’t make your users
type more than they
need to.
Do give buttons for
responses.
Sorry, I don’t understand
‘mauve’. You must type
‘Yes please I want a
mauve sofa’ or ‘Yes
please I want a blue
sofa.’

58. Don’t repeat yourself

59. A conversation flow

64. • Provide multiple responses for each node.
• Detect repeat visits to a single node, and
do something about it.

65. “I can see this isn’t
going so well. Would
you like to talk to a
real person?”
Detect frustration,
and handle it.

66. Watson
Speech to Text
Watson
Conversation
React.js
client
Bluemix
weather
service
WebSphere
Liberty
PDFs
Public Internet
IBM Bluemix
Example architecture for a socially sensitive bot
Watson
Sentiment
Analysis

67. Context is important

68. How complex the conversation
gets is up to you.

69. Should your chatbot
admit it’s not a person?
Cunning human-
like disguise

70. Annoying: Hoping to talk to a human,
and talking to a bot.
More annoying: Believing you’re talking
to a human, then realising it’s a bot.

71. You need a lot of automated tests -
and you should write them first

72. Devops still matters.
Tests.
(Lots of tests.)
Conversation
representation.
Application
Source
controlled
inputs
Generation

73. A good devops
flow for
workspaces.
Development
Conversation
instance
Test
Conversation
instance
Production
Conversation
instance
Workspace
json
Source
control
Developers,
UX designers,
and business
User
(not seeing
regressions )

74. Then, observe your users

75. If a chatbot isn’t usable, it’s nothing.

76. edkjdflk fehfs fhfiuhf
My credit card has been
stolen! I need to cancel it. How smart
are you?
Tell me a joke.
Real user
Test user
Your test users may
not be representative.

77. Test, Monitor, Tune

78. Record your logs. Then look at them.

79. Even if they know a bot is a bot,
users may treat it like a person.
Stuff stuff
reply …
Argh! You
piece of
%@*&@!
Ooh, I don’t
like that
language very
much.
Oh, sorry!

80. Continuous
feedback
Machine
learning

81. @holly_cummins
https://www.ibm.com/devops/method/
Chatbots are
awesome - but
remember, the
user has to come
first.