The document discusses cultivating creativity in data work. It argues that data science includes elements of science, art, and design. Design research methods can be leveraged to teach students the process of data science. The "art" of data science involves the skilled use of empathy, which can be developed through practices like design thinking, meditation, and design sprints. Teaching data science could borrow from design school curricula by emphasizing hands-on learning of tools and using non-judgmental, solution-focused processes.

1. CULTIVATING CREATIVITY
IN DATA WORK
HILARY PARKER

5. CULTIVATING CREATIVITY
IN DATA WORK

6. You’ve told me everything NOT to do,
but how will I know what to do?
Anonymous Roger Peng student

8. http://r4ds.had.co.nz/explore-intro.html

9. “Data Science is an art”

10. https://leanpub.com/artofdatascience
“Data analysis is hard, and part of
the problem is that few people can
explain how to do it. It’s not that
there aren’t any people doing data
analysis on a regular basis. It’s that
the people who are really good at it
have yet to enlighten us about the
thought process that goes on in
their heads.”

11. https://www.slideshare.net/ElsevierConnect/zen-and-the-art-of-data-science-maintenance/1

12. https://www.slideshare.net/ElsevierConnect/zen-and-the-art-of-data-science-maintenance/1

14. “The demand for this “right” brain thinking is
increasing and in era of increased automation,
the need for the “art” of data science will be the
increasing cry of business.”

15. If data science is an art,
why don’t we teach it like
art?

19. MUSIC THEORY ::
INSTRUMENT ::
COMPOSITION ::
THEORY
PROGRAMMING LANGUAGE
NARRATIVE

20. My experience of the
field

21. Theory

22. Theory

23. Programming
Language

24. We may find that the two bottlenecks are what you want
to do, and how you tell the computer to do that. A lot of
my existing work…has been more about how to make it
easier to express what you want.
Hadley Wickham
https://statr.me/2013/09/a-conversation-with-hadley-wickham/

25. Teach students tools that
allow for fluency

26. Programming
Language

27. Narrative

28. Narrative

29. My experience in tech

30. Product
Development

37. Design sprints for data science

38. Design as a Discipline

39. Design ability is, in fact, one of the three fundamental
dimensions of human intelligence. Design, science, and
art form an ‘and’ not an ‘or’ relationship to create the
incredible human cognitive ability.”
Nigel Cross

40. Design ability is often treated
as “mythical” and a “mysterious
talent”

41. https://leanpub.com/artofdatascience
“Data analysis is hard, and part of
the problem is that few people can
explain how to do it. It’s not that
there aren’t any people doing data
analysis on a regular basis. It’s that
the people who are really good at it
have yet to enlighten us about the
thought process that goes on in
their heads.”

42. Design process is
solution-focused, versus
problem-focused

43. You’ve told me everything NOT to do,
but how will I know what to do?
Anonymous Roger Peng student

44. Design is constructive thinking
-- you need to start building
solutions to understand the
problem fully

46. Design process employs both
the left-brain and the
right-brain.

47. “The demand for this “right” brain thinking is
increasing and in era of increased automation,
the need for the “art” of data science will be the
increasing cry of business.”

48. Though the field did have a
“scientific design” movement in
the 60s, it has mostly moved
on from cookbook methods

49. Gosset to Pearson in 1905
From “Guinnessometrics: The Economic Foundation of “Student’s” t” by Stephen T.
Ziliak

50. Design is a form of non-verbal
rhetoric, with sketching as the
language

51. One thing that is clear is that sketches enable designers
to handle different levels of abstraction simultaneously…
Clearly this is something important in the design process.
We see that designers think about the overall concept and
at the same time think about detailed aspects of the
implementation of that concept.
Nigel Cross

52. http://r4ds.had.co.nz/explore-intro.html

53. Teaching Design

54. Teach design as a fundamental process
that is independent of theory
Borrow on design school curricula
Employ design methods such as design
sprints

55. The Role of Art?

56. What is success in Data
Science / Analysis?

57. A-HA

58. A data analysis is successful if the
audience to which it is presented
accepts the results.
Roger Peng
https://simplystatistics.org/2018/04/17/what-is-a-successful-data-analysis/

59. THE A-HA MOMENT
▸ Observable only from the first-person
perspective

60. THE A-HA MOMENT
▸ Observable only from the first-person
perspective
▸ Third person observers can only rely on
accounts

61. THE A-HA MOMENT
▸ Observable only from the first-person
perspective
▸ Third person observers can only rely on
accounts
▸ People are unreliable about communicating
their experiences

62. COMMON ADVICE
▸ “Think about your audience”
▸ “Build good partnerships”
▸ “Be a good communicator”
▸ …

63. Empathy

64. Empathy“the capacity to understand or feel what another
person is experiencing from within their frame of
reference, i.e., the capacity to place oneself in
another's position.”
https://en.wikipedia.org/wiki/Empathy

65. Design sprints (and other design processes)
People are most willing to share when they don’t
feel judged
Listening to and understanding stakeholders is a
key part of creating solutions for them

66. Design sprints (and other design processes)
Most have rules for “playing nice”
▸ Non-judgmental observation
▸ Ideas originate from stakeholder interviews
▸ Require listening to and validating other
people’s opinions

67. Cultivating empathy

68. My experience with Zen
Buddhism

70. San Francisco
Zen Center

71. Zazen
Central practice of Zen Buddhism

72. Zazen
Central practice of Zen Buddhism
“Sitting meditation”

73. Zazen
Central practice of Zen Buddhism
“Sitting meditation”
Cultivating the ability to observe yourself
non-judgmentally, and with curiosity

74. Zazen
Central practice of Zen Buddhism
“Sitting meditation”
Cultivating the ability to observe yourself
non-judgmentally, and with curiosity
Acceptance practice

75. Zazen
Cultivate this acceptance with yourself, and it will
increase your capacity to observe, accept, and be
connected to others.

76. Empathy / “Art” in Data Science
Accepting the audience where they are right now -- their
educational context, their biases, their motivations

77. Empathy / “Art” in Data Science
Accepting the audience where they are right now -- their
educational context, their biases, their motivations
Accepting yourself where you are right now -- your biases,
your preferences, your blind spots

78. Empathy / “Art” in Data Science
Accepting the audience where they are right now -- their
educational context, their biases, their motivations
Accepting yourself where you are right now -- your biases,
your preferences, your blind spots
Employing modes of communication other than scientific
communication

79. In conclusion:

80. Data science includes all three forms of human
cognition: science, art, and design

81. Data science includes all three forms of human
cognition: science, art, and design
Design research can be leveraged for teaching
students the “how” of data science

82. Data science includes all three forms of human
cognition: science, art, and design
Design research can be leveraged for teaching
students the “how” of data science
The “art” of data science is the skilled use of
empathy, which can be cultivated

83. THANKS!

84. Appendix: Resources

85. Designerly Ways of Knowing / Design
Thinking (Nigel Cross)
Nigel Cross is one of the primary academics
working on “Design as a Discipline”. He is also a
superb writer, and writes about the field in a very
accessible way. I read Designerly Ways of Knowing,
however I am told that Design Thinking is very
similar content. Additionally, each chapter of
Designerly Ways of Knowing is an article, so it is
possible to get access to those without purchasing
the book.

86. Sprint (Jake Knapp)
This book outlines the design sprint process, and
has several case studies of sprints working (and not
working) at various startups. It’s an enjoyable quick
read that introduces one structured approach to
design thinking.

87. Designing Your Life (Bill Burnett and Dave
Evans)
This book is also taught as a very popular class
from the Stanford d.school. I found it extremely
helpful for establishing a “design mindset” in a
relatable way. Additionally, I think there is added
benefit to helping students view their academic /
work life in a non-judgmental way. I highly
recommend introducing this to students, even
though it is not related to statistics per se.

88. Articulating Design Decisions (Tom
Greever)
This book would be most helpful for students who
want to enter the tech industry, but would also be
helpful for everyone. It outlines the different
contexts and motivations that people in various
roles within the tech industry might have (e.g.
CEOs are very results-driven rather than
problem-driven). The applicability of this book to
data science underscores how conceptually similar
the fields of design and data science are.

89. The Art of Data Science (Roger Peng and
Elizabeth Matsui)
This book discusses the “how” of doing data
science, and includes several examples. Roger and
Elizabeth are great writers, and it is a fun and
accessible read!

90. Statistics as Principled Argument (Robert
Abelson)
This book approaches statistics in a “design
thinking” way. I don’t have as many comments as I
haven’t dug into it, but I am intrigued by people in
the field approaching statistics as rhetoric /
argument!

91. The Field Guide to Understanding Human
Error (Sidney Dekker)
I didn’t talk about Blameless Postmortems in this
talk, but have covered them in previous
presentations (one, two) and in the paper
“Opinionated Analysis Development”. Blameless
Postmortems present another structured,
non-judgmental paradigm shift for designing
processes (versus products). I find them extremely
useful for discussing statistical tools such as
programming language choices, and think they
would be another very valuable thing to teach to
introductory students.

92. Stitch Fix Data Science
Some folks on the Analytics & Algorithms team at
Stitch Fix created an interactive visualization of the
various ways that we use data science at the
company. Some teachers have found it helpful to
use Stitch Fix as an example of applied statistics in
a non-traditional field, and I have to say I’m quite
supportive of this! =)

93. 10% Happier (Dan Harris)
This is a very accessible introduction to meditation
from a news anchor who came to it in a very
skeptical way. I found it be extremely relatable and
a great introduction to meditation and the various
communities (including the Zen Buddhist
community) who practice meditation.

94. San Francisco Zen Center
I live and practice with my partner at the San
Francisco Zen Center. They have a number of
online programs (including an “online zendo” --
practicing meditation in a group on a Zoom video
chat!). This is a great resource if you are interested
in Soto Zen Buddhist community and practice.