This document discusses privacy challenges related to emerging technologies like big data, merged realities, and cognitive computing. It provides an overview of these technologies and their implications for privacy. The role of information professionals in addressing privacy issues is also examined. Key points discussed include how new technologies often conflict with privacy, the global scale of data collection, and how technology could also help manage privacy concerns.

1. Privacy,
Emerging
Technology,
and
Informa6on
Professionals
Mike
Smit
School
of
Informa-on
Management
Faculty
of
Management
@michael_smit

2. Emerging
Technology
Direc6ons
Privacy
&
Emerging
Technology
Role
of
Informa6on
Professionals

3. Privacy
&
Emerging
Technology
3

4. Morning
Quiz:
In
which
decade
did
each
of
the
following
quotes
originate?

5. “Almost
inevitably,
transferring
informa6on
from
a
manual
file
into
a
computer
triggers
a
threat
to
civil
liber6es,
to
privacy,
to
a
man's
very
humanity
because
access
is
so
simple.”
Alan
Wes-n,
1970

6. “Recent
inven6ons
and
business
methods
call
aNen6on
to
the
next
step
which
must
be
taken
for
the
protec6on
of
[privacy].”
Warren
&
Brandeis,
1890

7. “…[Web]
privacy
issues
are
a
red
herring.
You
have
zero
privacy
anyway.
Get
over
it.”
ScoE
McNealy,
1999

8. “When
the
details
of
our
lives
are
fed
into
a
central
computer
or
other
vast
file-­‐keeping
system,
we
all
fall
under
the
control
of
the
machine's
managers
to
some
extent.”
Vance
Packard,
1964

9. “People
have
really
goNen
comfortable
not
only
sharing
more
informa6on
and
different
kinds,
but
more
openly
and
with
more
people…
That
social
norm
is
just
something
that
has
evolved
over
6me.”
Mark
Zuckerberg,
2010

10. “With
the
advance
of
technology,
centralized
data
accumula6on
becomes
easier,
the
reward
for
intrusion
is
increased,
and
control
shiYs
to
s6ll
fewer
people.”
Jerry
M.
Rosenberg,
1969

11. Novel
technologies
oYen
conflict
with
privacy.
11

12. Novel
technologies
oYen
conflict
with
privacy.
12

13. Two
Specific
Modern
Challenges
Global
Scale
13

14. Technology
can
help
manage
privacy.
14

15. 15

16. • Big
Data
• Merged
Reali-es
• Cogni-ve
Compu-ng
Emerging
Technology
Direc6ons
16

17. Caveats
• "There
is
no
reason
anyone
would
want
a
computer
in
their
home.”
– Ken
Olson,
president,
chairman
and
founder
of
Digital
Equipment
Corp.,
1977
• "Two
years
from
now,
spam
will
be
solved.”
– Bill
Gates,
founder
of
Microso`,
2004
• “I
predict
the
Internet
will
soon
go
spectacularly
supernova
and
in
1996
catastrophically
collapse.”
– Robert
Metcalfe,
founder
of
3Com,
1995
17

18. Gartner
Hype
Cycle
18

19. BIG
DATA
19

20. Gartner
Hype
Cycle
20

21. What
is
Big
Data?
• Volume
/
Variety
/
Velocity,
or
• Anything
more
than
you
can
handle,
or
• Data
measured
in
TB
or
bigger,
or
• Anything
I
have
a
beEer
chance
of
selling
you
by
claiming
it
is
Big
Data.
21

22. What
is
Big
Data?
• Volume
/
Variety
/
Velocity,
or
• Anything
more
than
you
can
handle,
or
• Data
measured
in
TB
or
bigger,
or
• Anything
I
have
a
beEer
chance
of
selling
you
by
claiming
it
is
Big
Data.
WHY
is
Big
Data?
22

23. Reason
#1:
Web
2.0
turned
everyone
into
content
creators

25. Reason
#2:
Internet
of
Things
turns
everything
into
data
creators
Image:
GE
press
release

26. Reason
#3:
Data
accumula6on
is
less
visible
26

28. Reason
#4:
Declining
price
of
storage

29. 1.
How
much
would
it
cost
to
buy
enough
hard
drives
to
store
all
the
music
in
the
iTunes
store?
2.
How
much
space
will
I
need
for
all
those
hard
drives?
3.
Same
ques6ons,
but
pretend
it
is
10
years
ago.

30. Reason
#5:
Cloud
storage
(and
pay-­‐
as-­‐you-­‐go
pricing)

31. Pre-­‐Cloud
0
1
Price
Time
31

32. Cloud
Era
0
1
Price
Time
32

33. Ds1fFtZx4olD5acndKSToGizuuj2D9Ut9prJlDLPpq35mNVHQghsD
pGo13qZKpgF8Qe1xQnjKU0VEDwn3aXNTe4miEwbAq2WqkjWx
2NZSH70kdK4x3h7L6E6DlnZrZeOlBZLXlFcCklu`Scz0Ei13tqpALV
vObQ3BnepwdPUpFSMnqvYaSQ4P3F6We9zXKIZDb-PGl8yyDw
6XEAEMUcAq8mR4Z9WOY3XZG8b9QGwINtRMeTdKosHnTobzw
f4gFFszjx1E0EJA22up0zg8Ub35gEd8wHc7yTmTZWZMU6hBVsEz
hzcTaWx2wlYHstAiYjRAIAoYbuNupw0iWaxweJaCWl9y8J5zZ05Y
wTlAsh6jAl0Mp2RIkL3F00if8GGt3kaAzT5VQLHZSV1rJSTdMt9g1l
dQsPm5U95oZN3Cx9B8sHbsgNINq5yiMjuVlO3rkCd1ShH210wG
aIIlLpZ41U2$gK2fCEY5rvKU0p5sQHuIizchKc2zuGGP2FAZ3utFXh
XLDIyhdzExe9VKo8DtAQqprlBOrkvdMjVWAs2Jj6H9GW4LrrFZrX
Y3VC6h6v3pZkDcfwmT6jRwkJrwvbuFCq0t4vOUBjPeSggukZKFAs
1IryTkYKTPsJN5Lf5ZXhOqOcc9MB5MnkMAS1yqD5ayDv8kWW
W29hLFRiSLF6zkEQA95yer84R91Lt3dfglI2yamX4UDO7j18ocflm
cu9zfLklOLbR4Kg63GIvbfafqpv7wcNlBZ3Q3vJsjTmlbR6Is6kIlh3B
QIF3W1QWosPhG9oNmR3bzTfK5gACtmgmBTAtKNrtRIK4XAfpR
wmUZnBLYWJcjGIgjpD5237WhfZMFSEaMfOSi5SFD1aAq12D0c
Reason
#6:
The
lingering
hope
of
finding
valuable
informa6on

34. The
Challenge:
Big
Data
Hubris
34

35. 35

36. 36

37. 37

38. Why
Do
We
Have
Big
Data?
…
because
we
can.

39. What
is
Big
Data?
A
Problem,
not
a
Solu8on.

40. MERGED
REALITIES
40

41. What
is
this
made-­‐up
term?
• The
merging
of
the
online
world
and
the
physical
world.
Includes:
– Internet
of
Things
– NFC
– New
input
/
output
features
– Convergence
of
desktop,
laptop,
and
mobile
technology
– Quan-fied
self
– Autonomic
systems
– Prevalence
of
wireless
41

42. 42

43. What
is
this
made-­‐up
term?
• The
merging
of
the
online
world
and
the
physical
world.
Includes:
– Internet
of
Things
– NFC
– New
input
/
output
features
– Convergence
of
desktop,
laptop,
and
mobile
technology
– Quan-fied
self
– Autonomic
systems
– Prevalence
of
wireless
43

44. 44

45. Gartner
Hype
Cycle
45

46. 46

47. 47

49. COGNITIVE
COMPUTING
49

50. 50

51. Cogni6ve
Compu6ng
• Dealing
with
problems
like
a
human
might
– Work
with
natural
language,
unstructured
data
• Both
analysis
&
interac-on
– Aware
of
context
– Move
beyond
analysis
to
predic-ng
/
inferring
– Adapt
to
user
requirements
/
changing
data
• Provide
“decision
support”
51

52. Gartner
Hype
Cycle
52

53. 53

54. Role
of
Informa6on
Professionals
54

55. At
the
-me
of
being
admiEed
as
a
member
of
the
medical
profession:
I
solemnly
pledge
to
consecrate
my
life
to
the
service
of
humanity;
I
will
give
to
my
teachers
the
respect
and
gra-tude
that
is
their
due;
I
will
prac-ce
my
profession
with
conscience
and
dignity;
The
health
of
my
pa-ent
will
be
my
first
considera-on;
I
will
respect
the
secrets
that
are
confided
in
me,
even
a`er
the
pa-ent
has
died;
I
will
maintain
by
all
the
means
in
my
power,
the
honour
and
the
noble
tradi-ons
of
the
medical
profession;
My
colleagues
will
be
my
sisters
and
brothers;
I
will
not
permit
considera-ons
of
age,
disease
or
disability,
creed,
ethnic
origin,
gender,
na-onality,
poli-cal
affilia-on,
race,
sexual
orienta-on,
social
standing
or
any
other
factor
to
intervene
between
my
duty
and
my
pa-ent;
I
will
maintain
the
utmost
respect
for
human
life;
I
will
not
use
my
medical
knowledge
to
violate
human
rights
and
civil
liber-es,
even
under
threat;
I
make
these
promises
solemnly,
freely
and
upon
my
honour.
abra
Informa6on
professionals
and
technical
experts
have
a
responsibility
to
society.

56. Excuse:
“But…
privacy
is
a
personal
choice!”

57. 57

58. Excuse:
“Society
has
to
decide
to
make
privacy
a
priority,
not
us.”

60. Excuse:
“Focusing
on
privacy
discourages
innova6on!”

61. Hype
Cycle
Time
Expectations
Peak of inflated expectations
Trough of disillusionment
Slope of enlightenment
Plateau of Productivity
61

62. Regret
Cycle
Time
Expectations
Valley of Regret & Despair
Bank of Best Practices
Tundra of Technology Adoption
Mountain of Mistakes
62

63. Minimizing
Regret
Time
Expectations
Valley of Regret & Despair
Bank of Best Practices
Tundra of Technology Adoption
Mountain of Mistakes
63

64. Excuse:
“But
I
don’t
know
much
about
technology!”

65. We
adopt
new
technology
before
we’re
ready…
65

66. …
and
just
hope
it
all
works
out.
66

67. 67

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?
Informa6on
professionals
need
to
ask
the
right
ques6ons.

69. Sample
Ques6ons
From
the
Top
of
my
Head
• How
will
it
change
our
organiza-on
of
informa-on?
• Will
exis-ng
structures
and
informa-on
architectures
need
systemic
changes?
What
types
of
changes
do
you
an-cipate?
• Will
this
have
implica-ons
for
how
informa-on
is
stored?
Retrieved?
Indexed
&
searched?
• Will
new
processes
or
controls
be
required?
• What
addi-onal
evalua-on
/
repor-ng
might
be
required?
• What
new
types
of
informa-on
will
appear,
or
become
more
prevalent,
due
to
this
technology?
• What
value
will
an
effec-ve
informa-on
management
plan
add
to
the
adop-on
process?
What
is
the
case
for
alloca-ng
resources
to
effec-ve
informa-on
management?
• What
quality
of
informa-on
is
produced
by
this
technology
(e.g.
is
there
lots
of
duplica-on,
or
no
consistency,
or
data
that
quickly
becomes
stale)?
What
quality
of
informa-on
is
required?
Is
informa-on
quality
improved?
• What
exis-ng
systems
might
become
obsolete?
What
exis-ng
systems
require
updates
or
upgrades?
Will
this
technology
require
integra-on
or
connec-on
to
exis-ng
systems
that
do
not
support
integra-on?
• Are
exis-ng
prac-ces
and
processes
sufficient,
or
will
educa-on
and
training
be
required?
69

70. “You
have
to
fight
for
your
privacy
or
you
lose
it.”
Eric
Schmidt
Execu-ve
Chairman,
Google

71. Discussion
• Mike.Smit@dal.ca
• @michael_smit
@michael_smit
//
#MarConnec-ons
71

72. 72

73. Image
Credits
(1)
• hEp://www.scien-ficamerican.com/media/inline/blog/Image/wisdom.jpg
• hEp://rudyloans.com/wp-­‐content/uploads/2013/11/Arrow-­‐Up-­‐4.jpg
• hEp://www.mrwallpaper.com/cat-­‐and-­‐dog-­‐cuddle-­‐wallpaper/
• hEp://poEermore.wikia.com/wiki/Category:Gryffindor
• hEp://poEermore.wikia.com/wiki/File:Slytherin_mark.png
• hEp://daverobertsfilm.wordpress.com/2011/02/02/media-­‐studies-­‐key-­‐debates/
• hEp://www.themobilityresource.com/wearable-­‐technology-­‐and-­‐how-­‐it-­‐affects-­‐
people-­‐with-­‐disabili-es/
• Original
source
unknown;
available
• hEp://adpaascu.wordpress.com/tag/global-­‐ci-zens/
• hEps://www.torproject.org/
• hEp://www.gnupg.org/
• hEp://www.iden-tyfinder.com/
73

74. Image
Credits
(2)
• hEp://www.gartner.com/technology/research/hype-­‐cycles/
• hEp://blog.udacity.com/2013/07/new-­‐course-­‐design-­‐of-­‐everyday-­‐things.html
• Screenshot
from
hEp://pennystocks.la/internet-­‐in-­‐real-­‐-me/
• hEp://www.officeimaging.com/
• hEp://www.clipartbest.com/gradua-on-­‐caps-­‐clip-­‐art
• Cost
per
GB
from
hEp://www.mkomo.com/cost-­‐per-­‐gigabyte-­‐update
• Images
on
slides
47,
57,
58
are
©
Mike
Smit,
2014.
• Slide
35:
screenshot
of
personal
laptop
&
cell
phone
• Slide
37:
Vancouver
Archives,
hEp://searcharchives.vancouver.ca/power-­‐lines-­‐
and-­‐suppor-ng-­‐structure-­‐in-­‐lane-­‐west-­‐of-­‐main-­‐street-­‐at-­‐pender-­‐street
• Slide
43:
Screenshot
of
Watson
User
Modeling.
Made
from
my
own
copy
of
their
demo
applica-on,
but
also
available
publicly
at
hEp://watson-­‐um-­‐
demo.mybluemix.net/
74

75. Image
Credits
(3)
• All
graphs
were
created
for
the
purpose
of
this
presenta-on
• Logos
on
slide
38
are
from
the
respec-ve
websites
• Images
on
slide
39:
– BoEom
le`:
Thalmic
Labs
via
TechCrunch
hEp://techcrunch.com/2013/06/05/thalmic-­‐labs-­‐
raises-­‐14-­‐5m-­‐to-­‐make-­‐the-­‐myo-­‐armband-­‐the-­‐next-­‐big-­‐thing-­‐in-­‐gesture-­‐control/
– Top
le`:
Apple.com
– Top
right:
fitbit.com
– BoEom
right:
hEps://www.google.ca/glass/start/
• Slide
41:
hEp://www.geekwire.com/2013/ibm-­‐takes-­‐watson-­‐cloud/
75