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Surveillance of Emergent Associations: Freedom of Association in a Network Society

Surveillance of Emergent Associations: Freedom of Association in a Network Society. Katherine J. Strandburg DePaul University College of Law. OUTLINE. “NETWORK EFFECTS”: A. EMERGENT ASSOCIATION B. TRAFFIC DATA TRACKING C. SOCIAL NETWORK ANALYSIS

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Surveillance of Emergent Associations: Freedom of Association in a Network Society

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  1. Surveillance of Emergent Associations: Freedom of Association in a Network Society Katherine J. Strandburg DePaul University College of Law

  2. OUTLINE • “NETWORK EFFECTS”: A. EMERGENT ASSOCIATION B. TRAFFIC DATA TRACKING C. SOCIAL NETWORK ANALYSIS • THE PARADOX OF CURRENT LAW A. SURVEILLANCE LAW’S NEGLECT OF TRAFFIC DATA B. FIRST AMENDMENT’S STRONG PROTECTION OF ASSOCIATIONS III. FOURTH AMENDMENT LESSONS FOR FREEDOM OF ASSOCIATION IV. APPLICATIONS TO NETWORK ANALYSIS OF TRAFFIC DATA

  3. I.A. “NETWORK EFFECTS”: EMERGENT ASSOCIATIONS • Internet + • Wireless technology + • Locational technology + • Social networks + • Video and audio technology = New potential for association - political, civic, social, educational, etc.

  4. I. “NETWORK EFFECTS” EMERGENT ASSOCIATIONS • Can form rapidly and cheaply • Link w/o rt distance, all sizes possible • Strategies can self-organize • Membership not specified or defined, pseudonymous ENORMOUS NEW POTENTIAL FOR EXPRESSIVE ASSOCIATION

  5. I.B. “NETWORK EFFECTS”: TRAFFIC DATA BUT . . . . • Takes place through communication intermediaries • Spontaneous association is recorded in voluminous amounts of traffic data • Telephone records • Internet traffic logs • Location tracking, etc. • New technologies of association also used by malevolent groups – terrorist, pedophiles INCREASING RELATIONAL SURVEILLANCE

  6. I.C. “NETWORK EFFECTS”: NETWORK ANALYSIS RELATIONAL SURVEILLANCE THROUGH NETWORK ANALYSIS OF TRAFFIC DATA Social Network Analysis and Network Science: Use relational patterns to determine: • Structure of organization • Divide populations into social groups • Understand roles played by different individuals • Using sophisticated data mining-type algorithms and large datasets

  7. I.C. NETWORK ANALYSIS RELATIONAL SURVEILLANCE THROUGH NETWORK ANALYSIS OF TRAFFIC DATA • Investigating structure of known networks • Targeted link analysis - investigate a “suspicious” individual’s associational affiliations • Pattern-based analysis - uncover associations using relational patterns - “match” to suspicious patterns

  8. I. “NETWORK EFFECTS” PROBLEMS W/ RELATIONAL SURVEILLANCE USING NETWORK ANALYSIS • EXPOSE LEGITIMATE ASSOCIATIONS • TARGETED LINK ANALYSIS EXPOSES ASSOCIATIONS OF NON-TARGETS • MANY PROBLEMS WITH ACCURACY • Problems are deep, esp. for pattern analysis, do “malevolent” associations really look different? • See many discussions of issues with data mining (Slobogin, Swire)

  9. OUTLINE • “NETWORK EFFECTS”: A. EMERGENT ASSOCIATION B. RELATIONAL SURVEILLANCE • THE PARADOX OF CURRENT LAW A. SURVEILLANCE LAW’S NEGLECT OF TRAFFIC DATA B. FIRST AMENDMENT’S STRONG PROTECTION OF ASSOCIATIONS III. FOURTH AMENDMENT LESSONS FOR FREEDOM OF ASSOCIATION IV. APPLICATIONS TO NETWORK ANALYSIS OF TRAFFIC DATA

  10. II.A. PARADOX OF CURRENT LAW FOURTH AMENDMENT: virtually no protection to traffic data - Focus on individual privacy • Third party doctrine • Content/non-content distinction • interception/stored records distinction SURVEILLANCE STATUTES: only a little better • Traffic data usually available by showing “relevance” to a law enforcement or terrorism investigation • sometimes little or no judicial oversight NETWORK ANALYSIS MAKES LOTS OF DATA POTENTIALLY “RELEVANT”

  11. II.B. PARADOX OF CURRENT LAW FIRST AMENDMENT: strong protection for expressive association - Boy Scouts v. Dale: broad definition of expressive association; deferential approach to association perceptions of harm • NAACP v. Alabama: compelled disclosure of membership list requires strict scrutiny under First Amendment • Sheldon v. Tucker: broad, indiscriminate disclosure of memberships cannot be required; disclosure must be tailored to to compelling gov’t interest

  12. II. PARADOX OF CURRENT LAW  Relational Surveillance Using Network Analysis = Disclosure Of Association Membership Lists, Esp. For EMERGENT ASSOCIATIONS • Relational Surveillance Threatens to Chill Emergent (and other) Association b/c Fourth Amendment fails to protect associational information • First Amendment has been applied only to traditional associations

  13. II. PARADOX OF CURRENT LAW NEED FIRST AMENDMENT APPROACH TO RELATIONAL SURVEILLANCE (CF. SOLOVE) NEED TO UPDATE FREEDOM OF ASSOCIATION DOCTRINE TO REFLECT CURRENT ASSOCIATIONAL PATTERNS AND DISCLOSURE MECHANISMS

  14. OUTLINE • “NETWORK EFFECTS”: A. EMERGENT ASSOCIATION B. RELATIONAL SURVEILLANCE • THE PARADOX OF CURRENT LAW A. SURVEILLANCE LAW’S NEGLECT OF TRAFFIC DATA B. FIRST AMENDMENT’S STRONG PROTECTION OF ASSOCIATIONS III. FOURTH AMENDMENT LESSONS FOR FREEDOM OF ASSOCIATION IV. APPLICATIONS TO NETWORK ANALYSIS OF TRAFFIC DATA

  15. III. FOURTH AMENDMENT LESSONS HOW TO ADAPT TO EVOLVING TECHNOLOGY ? • Law must adapt to change of situs of socially important activity (Katz) • Law must recognize that surveillance involves both gathering and analyzing data – both can implicate Constitutional values (Kyllo) • Intrusiveness of surveillance depends on discrimination between legitimate and illegitimate activity (“dog sniff” cf. Kyllo)

  16. III. FOURTH AMENDMENT LESSONS FREEDOM OF ASSOCIATION TEST for RELATIONAL SURVEILLANCE • Does the surveillance serve a compelling interest? • Is analysis sufficiently accurate in light of potential burden on association? • Is analysis sufficiently closely related to the compelling interest in light of potential burden on association?

  17. OUTLINE • “NETWORK EFFECTS”: A. EMERGENT ASSOCIATION B. RELATIONAL SURVEILLANCE • THE PARADOX OF CURRENT LAW A. SURVEILLANCE LAW’S NEGLECT OF TRAFFIC DATA B. FIRST AMENDMENT’S STRONG PROTECTION OF ASSOCIATIONS III. FOURTH AMENDMENT LESSONS FOR FREEDOM OF ASSOCIATION IV. APPLICATIONS TO NETWORK ANALYSIS OF TRAFFIC DATA

  18. IV. APPLICATIONS TO NETWORK ANALYSIS Targeted Link Analysis: • Involves traffic data from target plus connected individuals • For Target: exposes numerous associations indiscriminately - Cf. Sheldon v. Tucker – high standard should be required (probable cause?) • For others: less intrusive, but also less relevant (depending on how many links away) - Relevance not enough - Reasonable suspicion?

  19. IV. APPLICATIONS TO NETWORK ANALYSIS Pattern-Based Analysis: • Involves traffic data from numerous individuals • Exposes broad swath of associations (mostly innocent) • Ability to distinguish malevolent associations questionable at best DOES NOT MEET FIRST AMENDMENT STANDARDS – NOT SUBSTANTIALLY RELATED

  20. IV. CONCLUSIONS • Associations poised to play increasingly important role in democracy and culture b/c of Internet, etc. • Traffic data increasingly permits relational tracking • Fourth Amendment fails to protect traffic data b/c focus is on individual privacy • Freedom of association strongly protects traditional associations • Need to update freedom of association law to regulate relational surveillance using traffic data

  21. IV. CONCLUSIONS • Pattern-based network analysis: • Does not meet 1st Amendment standards • Targeted Link Analysis • Should require probable cause for target • Reasonable suspicion for “links” • Individual traffic data • Case by case analysis • some cases may implicate First Amendment prohibition

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