The document outlines a project by the University of Cambridge focusing on predictive data and ambient intelligence in behavioral science, analyzing digital footprints from various social media to predict psychological traits. It presents findings from the largest audit of public opinion on big data, revealing concerns about privacy and the ethical use of personal data while noting the differing attitudes between marketing professionals and the general public. The study highlights the imperative for transparency and ethical guidelines to foster trust in predictive technologies.

1. PREDICTIVE DATA &
AMBIENT INTELLIGENCE
U N I V E R S I T Y O F C A M B R I D G E P S Y C H O M E T R I C S C E N T R E
A N D E D E L M A N
J U N E 2 0 1 6

2. To establish the University of
Cambridge as an international centre
of excellence in computational
behavioural science
M I S S I O N

3. PREDICTING PSYCHOLOGY FROM
DIGITAL FOOTPRINTS
FACEBOOK LIKEIDS
FACEBOOK STATUSES
TWEETS
BROWSING DATA
OPEN TEXT
AND MORE…
DEMOGRAPHICS
o Age
o Gender
o Relationship status
o Location
o Big 5 Personality
o Intelligence
o Life Satisfaction
o Political Views
o Religious Views
o Sexuality
o Profession
o Risk Propensity
The trait prediction engine is based on actual psychological data and the corresponding social media profiles of over 6 MILLION individuals.
INDIVIDUAL INSIGHTSDIGITAL FOOTPRINTS
APPLY MAGIC
SAUCE
PSYCHOGRAPHICS

4. SOCIAL SCIENCE
T H E L A R G E S T A N D M O S T R I C H S O C I A L S C I E N C E D A T A B A S E I N
H I S T O R Y , C O N T A I N I N G R I C H P S Y C H O - D E M O G R A P H I C P R O F I L E S
O N T H E A U D I E N C E S O F O V E R 2 0 0 , 0 0 0 B R A N D S
Over 6 MILLION unique
participants
Data shared with 150
academic collaborators
Responses to 25-30
validated psychological
assessments
40+ peer-reviewed
publications since 2011
Privacy-preserving
INDIVIDUAL INSIGHTS
Better-than-spouse
personality prediction
published in PNAS
”The most interesting thing for me is the predictive power of a few minuscule
“likes,” revealing a person’s feelings about a current event, a friend’s haircut
or a picture of a dancing cat. Remarkably, from these little pixels of
disconnected opinion, a pattern-seeking computer can create a detailed
pointillist picture of each of us in all our individuality.

5. PREDICTIVE
DATA PROJECT

6. AN AUDIT OF PUBLIC OPINION ON BIG DATA
H O S T E D O N A D A T A D R I V E N P L A T F O R M : P R E D I C T I V E D A T A P R O J E C T . C O M
P R E D I C T I V E B I G D A T A
R E S E A R C H A I M S
To scientifically examine and monitor public attitudes towards predictive technologies.
To explore the diverse opinions and psychological attributes of global consumers, and marketing and communications professionals.

7. INTRODUCTION TO THE RESEARCH
T H I S I S T H E L A R G E S T A U D I T O F P U B L I C O P I N I O N O N B I G D A T A A N D P R E D I C T I V E
T E C H N O L O G I E S I N H I S T O R Y W I T H 34,267 PEOPLE ( A N D C O U N T I N G ) T H A T H A V E
E N G A G E D W I T H T H E P R E D I C T I V E D A T A P R O J E C T A S S E S S M E N T P L A T F O R M
13% (1,868) of the participants were
marketing or communications professionals
8, 877 people answered all questions,
including 20 personality items
A truly global sample; 43% Europe, 27% North
America, 15% South America. Top countries were
USA (23%), UK (8%) Brazil (7%) and France (5%)
Demographic data shows an average age of 30
(distribution 10-78); 54% male; 16% tech, 11%
education, 5% advertising, 4% financial services

8. CONSUMERS ARE CONCERNED
O N L Y 2 9 % T H O U G H T M O S T C O M P A N I E S W I T H A C C E S S T O T H E I R
P E R S O N A L D A T A U S E I T E T H I C A L L Y
AGE
BIG5 PERSONALITY GENDER
LOCATION
O U R D A T A S H O W S T H A T
C O N C E R N S A B O U T
P E R S O N A L P R E D I C T I O N S
A R E U N I V E R S A L
To scientifically examine and
monitor public attitudes towards
predictive technologies.
To explore the diverse opinions and
psychological attributes of global
consumers, and marketing and
communications professionals.
A clear, consistent message on
predictive data could therefore
resonate well with large segments
of the public without alienating
specific personality segments

9. BUT CONSUMERS ARE INDIVIDUALS
We found that people who are more accepting of predictive
technologies tended to also be more open-minded, cooperative
and extraverted than those who are more reserved on the topic.
This supports previous research:
People who trust the government also
tend to be more emotionally stable, more cooperative
and more extraverted
Zhou & Lu (2011): high extraversion and low neuroticism related to greater degrees of trust in digital technologies
Korukonda (2007): high openness and agreeableness negatively related to computer anxiety, while neuroticism was positively correlated.

10. ALIGNING SERVICE WITH DEMAND
YES 38%
YES 84%
NO 62%
NO 16%
0 20 40 60 80 100
47% felt it should be used to determine the price of car insurance
71% of patients were happy to share social media information with their doctor (add reference here)
Should predictive technologies be used to
improve thequality of healthcare, for example
by helping doctors to recommend personalised
nutrition and exercise plans?
Should predictive technologies
be used assess your eligibility
for a mortgage?

11. CONTRASTING PUBLIC
AND MARKETING
PROFESSIONAL OPINIONS

12. MARKETING PROFESSIONALS WANT MORE
9 4 % S A I D I T W A S I M P O R T A N T F O R T H E M T O U N D E R S T A N D T H E P S Y C H O L O G I C A L A T T R I B U T E S O F T H E I R C U S T O M E R S
7 8 % S A I D T H E I R O R G A N I S A T I O N N E E D S T O I N V E S T I N P R E D I C T I V E T E C H N O L O G I E S
YES 53%
YES 78%
NO 47%
NO 22%
0 20 40 60 80 100
NON-CMOS
CMOS
There’s also a gap in desire for personalisation using predictive technologies,
with 78% of CMOs saying Yes compared to 53% of non-CMOs

13. RISKS OF OVERESTIMATING PUBLIC DEMAND
9 4 % S A I D I T W A S I M P O R T A N T F O R T H E M T O U N D E R S T A N D T H E P S Y C H O L O G I C A L A T T R I B U T E S O F T H E I R C U S T O M E R S
7 8 % S A I D T H E I R O R G A N I S A T I O N N E E D S T O I N V E S T I N P R E D I C T I V E T E C H N O L O G I E S
50% CMOs think future behaviour can be
predicted accurately from personal data compared
to 36% non-CMO
62% CMOs have heard of the right to be forgotten
compared to 47% non-CMOs
Across all domains, marketing and
communications professionals (CMOs) were
more accepting of uses of predictive technologies
and found their adoption generally more desirable
than people who do not work in marketing
AWARENESS
ACCEPTANCE

14. AND THERE IS INEQUALITY IN TRUST
T H E P U B L I C ’ S S U S P I C I O N O F T H E U S E O F P E R S O N A L D A T A I S C L E A R
This lack of trust, and unease amongst consumers, could become a real problem –
unless we tackle it now through the adoption of best practices and the right ethical approaches
53
58
56 56
60
44
47
46 46
48
2012 2013 2014 2015 2016
• Percent trust in the four institutions of
government, business, media and NGOs, 2012 to 2016
Informed
Public
Mass
Population
12pt
Gap
9pt
Gap
in trust inequality--
which jumps to a
5-point increase
among the GDP5
3-point increase

15. Trust-Building Behaviors:
Concerns around Data, Quality and Security
for TechI m p o r t a n c e v s . p e r f o r m a n c e o f b e h a v i o r i n b u i l d i n g t r u s t i n a c o m p a n y
%
Importance
%
Performance Gap

16. PRIVACY, TRANSPARENCY
AND RELEVANCE

17. PRIVACY
P R I V A C Y I S T O P O F M I N D
58% (11,090) of people surveyed reported having not used a
popular digital service because of privacy concerns
27% would pay $3 a month to use Facebook without their
behaviour being recorded, given that the average revenue
per user is around $1.33/month
”The most interesting thing for me is the predictive power of a few
minuscule “likes,” revealing a person’s feelings about a current event, a
friend’s haircut or a picture of a dancing cat. Remarkably, from these little
pixels of disconnected opinion, a pattern-seeking computer can create a
detailed pointillist picture of each of us in all our individuality.

18. PERSONALISATION
of CMOs thought their customers’ experience
of their brand was highly personalised to
their individual attributes, whereas 55% of
non-CMOs thought this was the case
64%
66%
56%
of people would prefer to see
personalised advertising, assuming they
have to see some advertising
of people thought predictive technologies
should be used to personalise their online
and mobile experience

19. AMBIENT INTELLIGENCE
57% of people thought that smart
fridge data should be used to
recommend groceries to them when
they go shopping.
42% of people thought that the benefits
of smart appliances pre-ordering
groceries and adjusting room
temperature outweighed the privacy
risks related to the data generated on
patterns in their home life

20. THE BENEFIT OF TRUSTED DATA
W H A T H A P P E N S W H E N Y O U G E T I T R I G H T
ETHICS
BETTER DATA
BETTER
OFFERING
BETTER
BUSINESS
TRUST

21. THANK YOU
U N I V E R S I T Y O F C A M B R I D G E P S Y C H O M E T R I C S C E N T R E
A N D E D E L M A N
J U N E 2 0 1 6