This document discusses the opportunities and challenges of using cloud computing technologies in research. It begins with an overview of cloud computing, including the three layers of cloud services. It then explores how researchers can leverage various cloud applications, platforms, and infrastructures. However, it also notes several new ethical issues that arise regarding subject privacy, data security, ownership and control. The document suggests researchers and IRBs face conceptual gaps and policy vacuums in dealing with these issues as cloud technologies continue to evolve rapidly. It emphasizes the need for education, guidance and careful consideration of terms of service agreements.

1. Research, the Cloud, and the IRB:
NEW OPPORTUNITIES :: NEW CHALLENGES
Michael Zimmer, PhD
Assistant Professor, School of Information Studies
Director, Center for Information Policy Research
University of Wisconsin-Milwaukee
zimmerm@uwm.edu
www.michaelzimmer.org

2. • Anyone who has studied the history of
technology knows that technological change is
always a Faustian bargain
• Technology giveth and technology taketh away,
and not always in equal measure.
• A new technology sometimes creates more than
it destroys. Sometimes, it destroys more than it
creates. But it is never one-sided.
• Neil Postman
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3. Agenda
• What is Cloud Computing?
• Opportunities for Use in Research
• Ethical Dimensions
• Subject confidentiality & anonymity
• Data privacy & security
• Data ownership & stewardship
• Research integrity & authorship
• Conceptual Gaps & Policy Vacuums
• What can Researchers and IRBs do?
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4. What is Cloud Computing?
KEXINO (CC BY-NC-ND 2.0) http://www.flickr.com/photos/kexino/4202662815/
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5. What is Cloud Computing?
• On-demand, network-based access to computing
recourses
• Features
• Location independent; supports increased mobility
• Flexible, scalable, robust
• On-demand performance; big data processing
• Little (if any) local support or maintenance
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6. What is Cloud Computing?
• Milestones
• 1999 – Salesforce.com delivers enterprise services via the
web
• 2002 – Amazon Web Services (storage, computation, human
intelligence via the cloud)
• 2004 – Gmail reboots web-based email, follows with Google
Docs
• 2006 – Amazon’s Elastic Compute Cloud (EC2)
• 2007 – IBM shifts focus to the cloud
• Popularity
• As early as 2008, 69 percent of Americans were using
webmail services, storing data online, or otherwise using
software programs located on the web
• By 2011, 80% of Fortune 500 companies use IBM cloud
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7. 3 Layers of Cloud Computing
http://en.wikipedia.org/wiki/File:Cloud_computing.svg (CC BY-SA 3.0)
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8. Application Layer
• “Software as a service”
• Providing productivity applications via the Web;
no local software needed
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9. Platform Layer
• “Platform as a service”
• Providing application development platforms and
operating systems via the Web
• Can deploy applications without needing your
own infrastructure or distribution channels
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10. Infrastructure Layer
• “Infrastructure as a service”
• Provide computing infrastructure on demand
• Outsourcing servers, storage, network
equipment, processing power, data centers
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11. Research Opportunities for Cloud
Computing
• Application layer
• Most common and easiest application of cloud
• Data gathering, storage, collaboration
• Platform layer
• Hosted apps for recruitment & surveys
• Infrastructure layer
• Access to increased processing power for large-scale
research projects
• Some non-traditional uses
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12. Research Opportunities: Applications
• Data gathering using web-based survey
applications
• SurveyMonkey
• Zoomerang
• Qualtrics
• Typically used “in the wild”, sometimes
institutionally-bound
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13. Research Opportunities: Applications
• Data storage & sharing using cloud-based
applications
• Dropbox
• Box.net
• iCloud
• Communication & collaboration using cloud-
based applications
• Gmail, IM, Skype
• Google Docs, Office Live
• Wikis
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14. Research Opportunities: Platforms
• With skilled programmers, can build custom apps
to deploy via cloud-based platforms
• Subject recruitment and screening apps on Facebook
• Building and deploying test instruments within online
gaming platforms
• Monitoring and activity tracking apps on mobile device
platforms
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15. Research Opportunities: Infrastructure
• Leverage cloud-based computing infrastructures to
handle resource-intensive processing tasks
• Clinical trial data storage & processing
• Sharing extremely large databases
• Innovative, non-traditional use of cloud-based
processing “resources”
• ____@Home (distributed computing)
• Fold.It
• Amazon Mechanical Turk
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16. Fold.It
• Web-based puzzle video game to assist with
protein folding research
• Leverage millions of gamers to assist in data
processing
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17. Fold.It
http://fold.it/
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18. Fold.It
• Web-based puzzle video game to assist with
protein folding research
• Leverage millions of gamers to assist in data
processing
• Players produced an accurate 3D model of and
AIDS-related enzyme in just 10 days
• Researchers had been trying for 15 years
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19. Amazon Mechanical Turk
• Facilitates outsourcing of computational or other
mundane tasks
• Requesters post “Human Intelligence Tasks”
offering minimal fees
• Workers select tasks to complete for
micropayments
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20. Amazon Mechanical Turk
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21. 3 Layers of Cloud Computing
http://en.wikipedia.org/wiki/File:Cloud_computing.svg (CC BY-SA 3.0)
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22. Ethical Dimensions
• Subject confidentiality & anonymity
• Data privacy & security
• Data ownership & stewardship
• Research integrity & authorship
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23. Subject Confidentiality & Anonymity
• When recruiting subjects or collecting data with
cloud-based applications…
• Are IP addresses logged in such a way to allow re-
identification of subjects
• Using a Facebook app might provide researchers access
to unnecessary personal information
• Are cloud providers tracking data and usage
themselves? Delivering ads? Selling user data?
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24. Data Privacy & Security
• Critical concern of any cloud system, takes on even
more importance when dealing with subject data
• Are cloud-based communication and collaboration systems
using SSL encryption?
• Is data stored on cloud-servers encrypted?
• What is service’s policy regarding 3rd party access
• Advertisers
• Investigative inquiry vs. subpoena vs. warrants?
• Electronic Communication Privacy Act (ECPA)
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25. Data Ownership & Stewardship
• Who owns, and who controls (meta)data in the
cloud?
• Are you granting the cloud provider any license to use your
data or activities (for advertising, data mining, etc)?
• Can you ensure data remains in the U.S.?
• Can data be destroyed on demand, including backups?
• Can you ensure cloud provider won’t hold your data
“hostage”, or disappear?
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26. Research Integrity & Authorship
• Should researchers rely on cloud-based data
processing and analysis?
• Can you trust (or audit?) external/collaborative processing
platforms
• Ethical to use Mechanical Turk, or otherwise outsource
mundane tasks to unknown persons for nominal wages?
• Authorship claims?
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27. Ethical Dimensions
• Subject confidentiality & anonymity
• Data privacy & security
• Data ownership & stewardship
• Research integrity & authorship
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28. Conceptual Gaps & Policy Vacuums
• Emergence of new technologies often lead to
conceptual gaps in how we think about ethical
problems, and reveal policy vacuums for how we
should best address them
• Computer technology transforms “many of our human
activities and social institutions,” and will “leave us with
policy and conceptual vacuums about how to use
computer technology”
• “Often, either no policies for conduct in these
situations exist or existing policies seem inadequate.
• Jim Moor, “What is Computer Ethics?”
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29. Conceptual Gaps & Policy Vacuums
• The fluidity and complexity of cloud-based tools
and platforms creates potential conceptual gaps
• Are these ethical dimensions merely the same as before,
or fundamentally different due to the cloud?
• Does the nature of anonymity, privacy, consent, even
harm change when dealing with cloud-based research?
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30. Conceptual Gap: Privacy
• Presumption that because subjects make information
available on a cloud-based service, they don’t have an
expectation of privacy
• Researchers/IRBs might assume everything is always public, and
was meant to be
• Assumes no harm could come to subjects if data is already
“public”
• New ethical problems…
• Ignores contextual nature of sharing
• Fails to recognize the strict dichotomy of public/private doesn’t
apply in the 2.0 world
• Need to track if ToS/architecture have changed, or if users even
understand what is available to researchers
Nissenbaum, H. 2011. “Privacy in Context: Technology,
Policy, and the Integrity of Social Life”
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31. Conceptual Gap: Anonymity vs.
Identifiability
• Presumption that stripping names & other obvious
identifiers provides sufficient anonymity when
sharing data in the cloud
• Assumes only PII allows re-identification
• New ethical problems…
• Ignores how anything can potentially identifiable
information and become the “missing link” to re-identify
an entire dataset
• “Anonymous” datasets are not achievable and provides
false sense of protection
Ohm, P. “Broken promises of privacy: Responding to the
surprising failure of anonymization.” UCLA Law Review
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32. Conceptual Gap: Consent
• Presumption that because something is shared or
available without a password, the subject is
consenting to it being harvested for research
• Assumes no harm can come from use of data already
shared with friends or other contextually-bound circles
• New ethical problems…
• Must recognize that a user making something public
online comes with a set of assumptions/expectations
about who can access and how
• Must recognize how research methods might allow un-
anticipated access to “restricted” data
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33. Conceptual Gap: Harm
• Presumption that “harm” means risk of physical or
tangible impact on subject
• Researchers often imply “data is already public, so what
harm could possibly happen”
• New ethical problems
• Must move beyond the concept of harm as requiring a
tangible consequence
• Protecting from harm is more than protecting from hackers,
spammers, identity thieves, etc
• Consider dignity/autonomy theories of harm
• Must a “wrong” occur for there to be damage to the subject?
• Do subjects deserve control over the use of their data streams?
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34. Conceptual Gap: Human Subjects
• Researchers (esp. CompSci) often interact only
with datasets, objects, or avatars, thus feel a
conceptual distance from an actual human
• Often don’t consider what they do as “human subject”
research
• New ethical problems
• Must bridge this (artificial) distance between
researcher and the actual human subject
• Also consider other stakeholders within the complex
arrangement of information intermediaries
Carpenter, K & Dittrich, D. “Bridging the Distance: Removing the Technology Buffer and
Seeking Consistent Ethical Analysis in Computer Security Research”
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35. Conceptual Gaps & Policy Vacuums
• The fluidity and complexity of cloud-based tools and
platforms creates potential conceptual gaps
• Are these ethical dimensions merely the same as before, or
fundamentally different due to the cloud?
• Does the nature of anonymity, privacy, consent, even harm
change when dealing with cloud-based research?
• Leaving researchers & IRBs with considerable policy
vacuums
• How should researchers deal with using the cloud in their
projects?
• How should IRBs review them?
• And how can we ensure good research still gets done…
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36. What can Researchers & IRBs do?
- broadly
• Get educated, find recourses
• Events like today; PRIM&R
• Utilize disciplinary resources
• For example: “Ethical decision-making and Internet research:
Recommendations from the AoIR Ethics Working Committee”
• Keep up on research
• Utilize experts
• Look for guidance
• Increased attention hopefully will prompt guidance
from HHS and related regulatory bodies
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37. What can Researchers & IRBs do?
- practically
• Read and understand the Terms of Service
• Incorporate in risk analysis
• Include mention of cloud-based services in
consent forms
• Level of detail?
• Monitor/audit cloud services over life of project
• Have terms or practices changed?
• All this is new, complex, and difficult…
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38. • Anyone who has studied the history of
technology knows that technological change is
always a Faustian bargain
• Technology giveth and technology taketh away,
and not always in equal measure.
• A new technology sometimes creates more than
it destroys. Sometimes, it destroys more than it
creates. But it is never one-sided.
• Neil Postman
10/12/2012 Virginia IRB Consortium Conference 38

39. Research, the Cloud, and the IRB:
NEW OPPORTUNITIES :: NEW CHALLENGES
Michael Zimmer, PhD
Assistant Professor, School of Information Studies
Director, Center for Information Policy Research
University of Wisconsin-Milwaukee
zimmerm@uwm.edu
www.michaelzimmer.org