The View from Computation and Algorithms

Andrew OlneyUniversity of Memphis

This Session

• Una-May O’Reilly– MOOCs: Research collaboration, data privacy, and

the role of technology

• Shuangbao Wang– The illusion of privacy in an age of cyberinsecurity

• Solon Barocas– Big data and unexpected threats to privacy

My Background

• Research– Language, Education, AI

• Data– Video, Speech, Motion, Posture, Text, EEG,

Eyetracking, Learning, Decisions/Judgments

• Admin

MOOCdb (Una-May)

• Open-ended standard data description

• Enable cross-course analysis

Video (Shuangbao)

• Automated video content analysis (inVideo)– Audio: keywords/language patterns– Video: reference pictures/knowledge

• inVideo could be applied to provide rich data on videos, turn them into more effective learning tools, and improve MOOCs

Privacy Threats (Solon)

• Benefits– Scientific knowledge– Decision making– Self knowledge

• Privacy protections must be sufficient to enable benefits• Problems

– Anonymity is an oxymoron• An identifier is an identifier• De-anonymization• Inference

– Informed consent cannot be guaranteed– Tyranny of the minority – the Target case

• Risk assessment

Focus Questions

• Threats/harms– De-anonymization– Public perception/discouragement

• Potential value– Scientific knowledge– Decision making– Self knowledge

• What IRB should do

Deanonymization

• Encryption?

• Self-identification– AOL’s 4417749

• Cross-comparison – Netflix (external)– Target (internal)

Identifiability

• How much “encryption” is enough?– Time vs. set size

• Is it possible to guarantee?– Relative to data type– Relative to cross-comparison

Identifiable data types

• Important characteristics– Stationary– Distinctive

• Face• Vocal tracts• Movement• Word choice

Cross-comparison

Threats

• Deanonymization very real– Low dimensionality data set with “vanilla”

indicators

• “Real World” data makes it worse– More chance of cross-comparison– But this is where the interesting questions are

What should IRB do?

• Risk analysis – centered– Worst case scenario considered for

privacy/confidentiality breach

• How will data be shared– Is public ‘anonymized’ warranted?– Restricted-use

Questions?

http://andrewmolney.name