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Record W2618770897

The FTC, the Unfairness Doctrine, and Privacy by Design: New Legal Frontiers in Cybersecurity

2017· article· en· W2618770897 on OpenAlexaboutno aff
Stuart Lloyd Pardau, Blake Edwards

Bibliographic record

VenueJournal of business & technology law · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicLaw, Rights, and Freedoms
Canadian institutionsnot available
Fundersnot available
KeywordsDoctrineComputer securityInternet privacyBusinessLaw and economicsPolitical scienceLawComputer scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

Journal of Business & Technology Lawsubsequently settled. 16 As for LabMD, the legal battle goes on. 17 After almost three years of wrangling with the FTC, an administrative law judge granted LabMD dismissal in November 2015, but the Commission later overturned the judge's decision, concluding the administrative action, leaving LabMD with one final shot in a federal appeals court. 18 If the U.S. Eleventh Circuit Court of Appeals, the court that would likely hear LabMD's appeal, takes up the case on the merits, it would be the second major decision on the FTC's unfairness approach, possibly either setting a trend, if the Eleventh Circuit issues a ruling similar to the Third Circuit's in Wyndham, or creating a circuit split if the courts differ.However LabMD turns out, the two cases provide fertile ground for discussing the government's evolving role in policing cybersecurity, and highlights the necessity for businesses that handle or store consumers' personal information to pay very close attention to what the FTC says about privacy and cybersecurity.So what exactly does the FTC expect?This article's contention is that the answer to that question, in a phrase, is "privacy by design."Although it was first introduced by the Commission in a 2010 privacy report, privacy by design, or PbD, was created by the former privacy commissioner of the province of Ontario in Canada, and dates back to the mid-1990s. 19 Generally speaking, PbD is an admonition that entities think about privacy holistically; to imbed it not only in the processes and procedures of the enterprise, but to broadly socialize the concept so that it becomes part of the organizational DNA.Historically, privacy had been considered as presenting some intellectually interesting issues, but organizationally was much less of a priority: a "nice to have," but not a "need to have."Indeed, the very concept of a "Chief Privacy Officer" ("CPO") only started becoming more commonly accepted within the past ten to fifteen years, 20 and even to this day, despite the need, frequently remains less visible and more marginalized within the organization or may not even exist at all. 21

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.776
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.020
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.268
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2017
Admission routes1
Has abstractyes

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