It is not uncommon to see privacy regarded as a form of personal secrecy managed by restricting information egress: for many this has been the default response to GDPR. When considering state or corporate secrecy these models have some validity, or at least hold traction: for example, levels of security clearance, or physical control of documents. However, for people the value and meaning of data is often more critical than raw volume. It may be the case that less information is more problematic and damaging than more information; we may confide in strangers things that we would not say to colleagues or friends; and even the use of anonymous aggregated data may be counter to the interests of those about whom it is collected. These things are all obvious when considered explicitly, and even for corporate and governmental entities issues of reputational damage share many features with personal privacy. Yet the myths seem to persist in many technical ‘solutions’ to privacy and in day-to-day actions, not least the destruction of documents that contributed to the Windrush scandal. As technologists we need to understand the non-monotonic nature of privacy and offer support that is less about restrictions on data, but more about maintaining provenance, understanding and explaining the implications of data, and creating tools and mechanisms to allow long-term personal control.

1. being secure:
some myths of privacy and
personal security
Alan Dix
Computational Foundry
Swansea
http://alandix.com/

3. information
the bare bits

4. classic Shannon and Weaver

5. monotonic: I(A+B) ≥ max( I(A), I(B) )
(sub)linear: I(A+B) ≤ I(A) + I(B)

6. neutral
CEO
partner
family president?
friendscolleagues
enemies
clients

8. security
keeping stum

9. Security may be super-linear
S(A+B) > S(A) + S(B)
longitude
latitude
not too
bad
not too
bad
OK
TOP
SECRET
known
secret
knownsecret

10. onion layers of secrecy
general
officers
squadies
others
increasing
security

11. onion layers of secrecy
CEO
mgt
employees
others
cleaners
increasing
security

13. privacy
close and personal

14. Myth 1
our home is our castle

15. family
friends
colleagues
strangers
increasing
privacy?
onion layers of privacy?

16. strangers on the train

17. design implications/ideas
granny watch
death locked diaries

18. Myth 2
privacy as information flow

20. privacy may be non-monotonic
P(A+B) < P(A)
why
alone in
office
really
bad
not too
bad
ideal
OKknown
secret
knownsecret

21. think windrush

22. design implications/ideas
context
connected data
data loss matters

24. Myth 3
anonymity and aggregation

25. William Murphy CC-BY-SA
https://en.wikipedia.org/wiki/Where%27s_Wally%3F#/media/File:Where’s_Wally_World_Record_(5846729480).jpg

26. bumps on the road

27. design implications/ideas
transparent processing
inherited control?
provenance

29. take home
privacy is not just data control
think about
human value and
personal meaning