The foundational question for designing AI systems is: Who is doing the work? The human with help from the AI? Or the AI with help from the human? Once designers understand and become familiar with the differences of these modes of interaction, they can more confidently design modern systems that take advantage of AI APIs. Noessel literally wrote the book on Agentive Tech last year, and is working on the follow-up book about Assistant Tech. In this workshop participants gather into design pairs. Then short lectures explain the core concepts and start the creative ideas flowing, followed by integration exercises where participants put these ideas into action. Each team refines ideas across the day, and integrating these modes into a cohesive whole. Time allowing, teams are asked to volunteer to present the key ideas from their designs.

1. W H O I S D O I N G T H E W O R K ?
D E S I G N I N G A C R O S S M O D E S O F I N T E R A C T I O N W I T H A N A I
I N T E R A C T I O N 1 9
@chrisnoessel
@thebenremington
W E D N E S D AY 6 F E B 2 0 1 9 D I S C I P L I N E I N F L U X

2. @ C H R I S N O E S S E L
• 20+ years interaction design
• Interaction Design Institute Ivrea
• Microsoft Futures Prototyping Group
• scifiinterfaces.com, Make It So: Interaction Design
Lessons from Science Fiction (Rosenfeld Media
2012)
• About Face 4th Edition (2016)
• Designing Agentive Technology:
AI That Works for People (Rosenfeld Media 2017)
• Senior Lead Designer,
Watson Customer Experience, IBM

3. @ T H E B E N R E M I N G T O N
• Seattlite 1994–1996
• Multiple Career Rabbit Holes
• Urban Design at UC Berkeley
• General Assembly 2013
• Interaction Designer, Epsilon

4. S H A R I N G W O R K W I T H A N A I

5. C AV E AT 1 / 3

6. C AV E AT: W I T T G E N S T E I N ’ S L A D D E R
You build on a useful lie
To get to the nuanced truth

7. T H E “ L I E ” I S …
Structuring the human-AI relationship
is as simple as HABA-MABA
Humans are Better At / Machines are Better At

9. T H E M A P I S N O T T H E T E R R I T O RY

10. C AV E AT 2 / 3

13. T H I S I S M O S T LY A B O U T W H AT Y O U R P R O D U C T D O E S ,
L E S S A B O U T T H E I N T E R FA C E O R M I C R O I N T E R A C T I O N S

14. C AV E AT 3 / 3

15. Katerina Kamprani
“The Uncomfortable”

16. T H I S I S A L M O S T C E RTA I N LY W R O N G
http://bit.ly/DoingTheWorkFeedback

17. W H I C H A I ?

18. A I H A S F L AV O R S

23. Icon by Guilhem from the Noun Project
What if our software could
learn from its mistakes, and
let users correct it when it’s
wrong? How could it improve
over time to help them?
Machine
learning
Icons by Ryan Beck from the Noun Project
Could we save their persona
time and effort by predicting
their needs? How would we
surface options? How could we
not bother them?
Predictive
technologies
Icon by Aybige Aya from the Noun Project
If the environment could see
and understand things were
happening, what would it look
for? How might it use that to
help personas?
Computer
vision

24. Icon by Guilhem from the Noun Project
What if our software could
learn from its mistakes, and
let users correct it when it’s
wrong? How could it improve
over time to help them?
Machine
learning
Icons by Ryan Beck from the Noun Project
Could we save their persona
time and effort by predicting
their needs? How would we
surface options? How could we
not bother them?
Predictive
technologies
Icon by Aybige Aya from the Noun P
If the environment could s
and understand things w
happening, what would it
for? How might it use tha
help personas?
Computer
vision

25. A M O D E L O F U S E

27. image: GetNarrative

29. T H E H U M A N D O E S T H E W O R K

30. T H E H U M A N D O E S T H E W O R K

31. T H E H U M A N D O E S T H E W O R K

32. T H E A I D O E S T H E W O R K

33. T H E A I D O E S T H E W O R K

34. T H E Y S H A R E T H E W O R K

35. H U M A N G E T S H E L P

36. H U M A N G E T S H E L P

37. H U M A N G E T S H E L P
?

38. H U M A N G E T S H E L P

39. H U M A N G E T S H E L P

40. A G E N T I V E I S T H E N E W M O D E O F U S E

41. A G E N T I V E I S T H E N E W M O D E O F U S E

42. A G E N T I V E I S T H E N E W M O D E O F U S E

43. A M O D E L B A S E D O N W H O I S D O I N G T H E W O R K

44. D E S I G N I N G F O R A S S I S TA N T

46. The Education of Achilles
Giovanni Battista Cipriani
c.1776
A G O O D A S S I S TA N T H E L P S .
A G R E AT A S S I S TA N T H E L P S Y O U G E T B E T T E R .

48. tput
inputsee
think
do

51. W O R K I N G I N S C E N A R I O S
A scenario is a story that tells of…
1. a user
2. in a situation
3. encountering a problem
4. going through a number of see-think-do steps
5. to solve the problem

54. B R E A K

55. D E S I G N I N G F O R A N A G E N T

57. C A M E R A S W I T H O U T P H O T O G R A P H E R S

58. image: Roomba

59. VA C U U M S W I T H O U T VA C U U M - E R S
image: Roomba

60. image: Google

61. C A R S W I T H O U T D R I V E R S
image: Google

62. D O E S T H I N G S
O N U S E R S ’ B E H A L F
A G E N T I V E T E C H

63. image: Scarecrow / Paul Souders
image: ShotSpotter
A S B I G A S Y O U C A N T H I N K
image: Tertill

64. image: Scarecrow / Paul Soudersimage: Avy

67. B I T. LY / B O W T I E D I A G R A M

68. H A N D O F F A N D TA K E B A C K

69. Human initiates | AI initiates

70. R E H E A R S E & P R E S E N T

71. Y O U R E H E A R S E
• Teams have 3 minutes each to
present their designs to the room.
(Random selection: Names in a hat!)
• Pick your favorite or most surprising
designs.
• Rehearse as many times as you can.
Get it under 03:00.
• Don’t want to present? Use this time
to help us improve: http://bit.ly/
DoingTheWorkFeedback
G E T I T D O W N T O 3 M I N U T E S

72. Y O U P R E S E N T
• The prior team times the
current team.
• The current team draws the
next team.
• Since we don’t have enough
time for everyone to present,
please tweet a description to
me, tag @AgentiveTech.
A S M A N Y A S T I M E A L L O W S

73. Congratulations.

74. U X A B S O R B S A I
RIP Stephen Hillenburg

75. U X A B S O R B S A I

76. U X A B S O R B S A I

82. Q U E S T I O N S &
A N S W E R S
bit.ly/agentivebook
Follow @agentivetech, @chrisnoessel
http://bit.ly/DoingTheWorkFeedback