LAK16 privacy and analytics (2016)
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Transcript of LAK16 privacy and analytics (2016)
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http://bit.ly/DELICATE
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Learning Analytics
HE Managers see:• Promise vs. Concerns• Potential vs. Risks• Benefits vs. Cost• Purpose vs. Competitive Pressures• Intentions vs. Hesitations
• Leading to Confusion
HEIs: How to implement LA?
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Institutionalising LA
Recent set-backs in education:• (1) inBloom• (2) Snappet
Acceptance factors: Data subjects being sufficiently aware of the consequences of using the system, the validity and relevance of the results obtained, and the level of transparency of the data model.
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• $100 million investment • Aim: Personalized learning in public schools, through data & technology
standards • 9 US states participated, in 2013 data about millions of children
have been stored
Privacy as Show Stopper for LA
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Privacy as Show Stopper for LA
Ignoring the fears and public perception of the application of
analytics can lead to a lack of acceptance, protests, and even failure
of entire LA implementations.
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Related Research Work
Prinsloo & Slade (2013)Slade & Prinsloo (2013) Pardo & Siemens (2014) Prinsloo & Slade (2015) Hoel & Chen (2015) Sclater, Bailey (2015) Steiner, Kickmeier-Rust, Albert (2015)
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Related Policies
http://www.open.ac.uk/students/charter/essential-documents/ethical-use-student-data-learning-analytics-policy#
https://www.jisc.ac.uk/sites/default/files/jd0040_code_of_practice_for_learning_analytics_190515_v1.pdf
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Related Policies• HEI law on data collection in NL like in all
EU countries since Nuremberg trials (data collection allowed to improve education, clear purpose, consent, limited access)
• Engelfriet, A., Jeunink, E., Manderveld, J. (2015). Learning analytics onder de Wet bescherming persoonsgegevens. https://www.surf.nl/kennis-en-innovatie/kennisbank/2015/learning-analytics-onder-de-wet-bescherming-persoonsgegevens.html
• SURF follow-up report with use cases in preparation
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Research Ethics
Origins lie in post-WWII. – Milestones:
• Nuremberg Code (1949)• Helsinki Declaration (1964)• Belmont Report (1978)• 2000s: Biomedical Science• RRI (Responsible Research and Innovation)
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Facebook Study
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Privacy
• The right to be left alone (Westin 1968)• Informational self-determination (Flaherty
1989)• Informational, decisional, local privacy
(Roessler 2005)
• Privacy is not anonymity or data security!
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Privacy
Contextual Integrity vs. Big Data Research
Context bound information vs. Repurposing of data
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Who are the Bad Guys?
ME&
MY DATAGovernment? Commerce?
Education? Hackers & Bad Guys?
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Legal Frameworks
• EU Data Protection Directive 95/46/EC (automated processing of ‘personal data’)2016: General Data Protection Regulation (GDPR)
• Restricting the (re-)use of data vs. and contradicting• Big Data business models• European Data Retention Directive 2006/24/EC
(data storage for security purposes)
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Legal Frameworks
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Legal Frameworks
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Fears
• Power-relationship, user exploitation• Data ownership• Anonymity and data security• Privacy and data identity• Transparency and trust
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Power-relationship
• Tracking and id-ing users or citizens by state or corporations (e.g. insurance companies, banks, car manufacturers, etc.) = benefit not to the user!
• Power-relationship is asymmetrical
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Exploitation
• Free labour as business model of for-profit companies
• Crowd sourcing outside the „commons“
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Data Ownership
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Data Ownership
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Data Ownership
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Anonymity and Data Security
• No absolute anonymity or de-identification
• Integration of multiple data sources increase compromised personal identity
• Data stores are not 100% secure
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Privacy and Data Identity
• System identity vs. Social identity
• People approximated onto data models by probability
• Power: data subjects have no say in the design of data model
Arora, P. (2016). Bottom of the data pyramid: Big data and the global South, International Journal of Communication
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Transparency and Trust
• Assumption: more transparency = more trust• But: relationship is mostly asymmetrical
(individual vs. big corporation)• Transparency as instrument of control
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Introducing: DELICATE
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Introducing: DELICATE
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Introducing: DELICATE
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Introducing: DELICATE
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Call for Papers
Special Issue: Journal of HE Development (ZfHE)
Learning Analytics: Implications for Higher Education
http://bit.ly/1qXTaNzDeadline: 10 June 2016Publication date: Spring 2017