La privacy by design: un'analisi comparata nell'era digitale
Bibliographic record
Abstract
The Digital Age brings along some relevant changes for lawyers and jurists. As a matter of fact, modern technologies invention and their diffusion cause specific requirements in order to protect the right of privacy because of the huge collection of individual?s information. Today, the concept of privacy is changing: the right to be let alone evolves in personal data protection. The aim of this thesis is to propose and explain the innovative approach of privacy by design. This new methodology for privacy protection may be an efficient solution for technologies challenges and may increase law enforcement. The starting point is certainly the law and his power to conform technology with the regulative system. Privacy by design approach has as a goal to design and develop a system, a product or a service in a way that supports and materializes privacy principles, rules and values. Privacy measures are embedded into the design and the architecture of ICT systems and business practices. Privacy by design is characterized by proactive technical and organizational measures in time for preventing privacy infractions in each situation and for better safeguarding data collection and data security. The concept requires more respect for user privacy, keeping it central. The idea of privacy by design arose in Canada thanks to the Commissioner Ann Cavoukian and then became an international principle for privacy protection. It is even used by Federal Trade Commission and Canadians Commissioners in few procedures. Nowadays some norms explicitly require privacy by design; this is the case of the General Data Protection Regulation of the European Union published in 2016. The main goal of this work is to analyze the principle in a critical, comparative and interdisciplinary way, considering the historical point of view, the regulatory interventions and the case law. The analysis might be useful for understanding and implementing the approach in more countries, taking into account the benefits and the level of criticality. It is necessary to give some guidelines for the real implementation of privacy by design, looking at the future, and to find a norm that can be applied all over the word; in fact, it is urgent to find a global solution for privacy concerns. Privacy by design won?t be the unique solution for privacy protection, but it will be essential for his future. This principle will safeguard better individual rights through a coherent and whole method. Designing privacy-friendly the technology means guarantee the other fundamental rights even more
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".