2:45pm Dec1/2012 From Osgoode Hall of York University, Toronto Social Networking Media: Crowd Sourcing the Investigation Cst. Scott Mills, Corporate Communications, Social Media Officer, Toronto Police Service Steven Johnston, Crown Prosecutor, Special Prosecutions Branch, Alberta Justice • Social networking as part of the electronic footprint of a criminal case • Discovery of evidence • Understanding the digital profile of your witness • Using essential "old school" investigative techniques

1. Crowdsourcing the Investigation
Osgoode Professional Development
Technology Crime and Electronic
Evidence, December 1, 2012
Constable Scott Mills, Toronto Police
Service
Steven Johnston, Alberta Justice
Specialized Prosecutions

2. DISCLAIMER
The opinions expressed herein are those of the
writer/presenter and are not necessarily the
opinions of the Toronto Police Service, the
Attorney General of Alberta, or the those of
the Department of the Solicitor General and
Justice of Alberta.

19. Crowdsourcing
According to Wikipedia:
Crowdsourcing is a type of participative online activity in which an
individual, an institution, a non-profit organization, or company
proposes to a group of individuals of varying knowledge,
heterogeneity, and number, via a flexible open call, the voluntary
undertaking of a task. The undertaking of the task, of variable
complexity and modularity, and in which the crowd should
participate bringing their work, money, knowledge and/or
experience, always entails mutual benefit. The user will receive the
satisfaction of a given type of need, be it economic, social
recognition, self-esteem, or the development of individual skills,
while the crowdsourcer will obtain and utilize to their advantage
that what the user has brought to the venture, whose form will
depend on the type of activity undertaken".

20. Why does this matter?
• Impact on policing, investigations and court
• Trends
• Is it really new?

21. What’s old is new again

22. The digital footprint
Intentionally or not any person who is in public
creates a digitial footprint,
From CCTV’s to social media people create, both
intentionally and unintentionally a footprint in
the digital world which can be accessed by
people around the world.

23. Who is the Crowd?
Any person who wants to assist.
Software can run alone as the Crowd, i.e.
Tagging of photos.
The impact of privacy laws, while seemingly vast
are ultimately local. If Facebook Canada turns
off an app, it may be that in another country
the app is still on and fully useable.

24. Police and the Crowd
• First impact is decision to embrace – or not
• If investigation goes to Crowd, must have a
plan in place to deal with the amount of
information coming in, both good and bad.
• Verification.

25. Finding Data in Crowd
Youtube – witnesses discussing the case, video
being posted which police may not have had,
and ultimately the use of software and the
crowd lead to sources of information
Facial Recongition Software

26. Impact on Courts
Disclosure – how will it be managed?
Privacy Issues
Admissibility in Courts

27. Disclosure
Vast amount of data = proportional increase in
requirement to manage the data in disclosure

28. Privacy Issues
In wake of the Vancouver Riots, police sought to
use the ICBC drivers licences for background
information and use facial recognition
software.
BC Privacy Commissioner ruled this requires
judicial authorization.

29. Admissibility in Court
Alberta Justice Policy is to not use facial
recognition software
Not aware of use in Canadian Courts
Developing area of law – standards.

30. References
California v. Heard, Superior Court in the State
of California, Court No 2429070, June 2010;
ANSI/NIST-ITL Standards Data Format for
Interchange of Fingerprint, Facial and other
Biometric Information;
People v. Johnson, Court of Appeal, 5th District,
California – No. F046939, May 2006

31. Data Mining can be done by
computers acting alone
• Potential advantages include a more
“objective” evaluation of evidence
• Can find patterns where a person may not
• Can deal with much larger volumes of data
than a person
• “predictive policing”

32. Can an algorithym become RPG?
Already happening in private security context,
i.e. Credit Cards
What is impact for police/search issues