Crowdsourcing The Investigation Technology & Digital Evidence Symposium Osgoode Hall 2012

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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

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  • What has changed since?
  • Does the person become an agent? What about anonymnity. Many places take Crimestoppers tips in modern ways, but what about Facebook etc.
  • Louisiana v. Johnson, Court of Appeal of Louisiana, 4 th Circuit, Feb 10, 2010 – allegation that jurors were using own computers to do enhancement of photos.
  • Crowdsourcing The Investigation Technology & Digital Evidence Symposium Osgoode Hall 2012

    1. 1. Crowdsourcing the InvestigationOsgoode Professional Development Technology Crime and Electronic Evidence, December 1, 2012 Constable Scott Mills, Toronto Police Service Steven Johnston, Alberta Justice Specialized Prosecutions
    2. 2. DISCLAIMERThe 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.
    3. 3. CrowdsourcingAccording 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".
    4. 4. Why does this matter?• Impact on policing, investigations and court• Trends• Is it really new?
    5. 5. What’s old is new again
    6. 6. The digital footprintIntentionally 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.
    7. 7. 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.
    8. 8. 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.
    9. 9. Finding Data in CrowdYoutube – 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 informationFacial Recongition Software
    10. 10. Impact on CourtsDisclosure – how will it be managed?Privacy IssuesAdmissibility in Courts
    11. 11. DisclosureVast amount of data = proportional increase in requirement to manage the data in disclosure
    12. 12. Privacy IssuesIn 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.
    13. 13. Admissibility in CourtAlberta Justice Policy is to not use facial recognition softwareNot aware of use in Canadian CourtsDeveloping area of law – standards.
    14. 14. ReferencesCalifornia 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
    15. 15. 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”
    16. 16. Can an algorithym become RPG?Already happening in private security context, i.e. Credit CardsWhat is impact for police/search issues

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