When Data Protection by Design and Data Subject Rights Clash

Veale, Michael; Binns, Reuben; Ausloos, Jef

doi:10.2139/ssrn.3081069

Cited by 17 publications

(25 citation statements)

References 4 publications

(1 reference statement)

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“…It should be remembered, however, that the usability of encrypted data is very limited and thus the purpose of transferring the data may be thwarted as a result. 105 Moreover, the effectiveness of encryption as a safeguard relies on the belief that US intelligence agencies will not be able to penetrate the encryption.…”

Section: The Implications Of Schrems IImentioning

confidence: 99%

ASSESSING THE IMPLICATIONS OF SCHREMS II FOR EU–US DATA FLOW

Murphy¹

2021

ICLQ

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With the constant flow of data across jurisdictions, issues regarding conflicting laws and the protection of rights arise. This article considers the EU–US data transfer relationship in the aftermath of the decision in Data Protection Commissioner v Facebook Ireland and Maximillian Schrems where the Court of Justice of the European Union (CJEU) invalidated an EU–US data transfer agreement for the second time in just five years. This judgment continues the line of cases emphasising the high value the Court places on securing EU personal data in accordance with EU data protection standards and fundamental rights. This article assesses the implications of the ruling for the vulnerable EU–US data transfer relationship.

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Section: The Implications Of Schrems IImentioning

confidence: 99%

ASSESSING THE IMPLICATIONS OF SCHREMS II FOR EU–US DATA FLOW

Murphy¹

2021

ICLQ

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“…A major caveat is that DPIA results are not required to be publicly disclosed 93 . For this reason, legal experts have suggested giving third parties with algorithmic expertise (i.e., academic data scientists) information rights to assess the results of DPIAs and convey the information to individual data subjects 94 .…”

Section: Governments and Regulatorsmentioning

confidence: 99%

Barriers for Academic Data Science Research in the New Realm of Behavior Modification by Digital Platforms

2021

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The era of behavioral big data has created new avenues for data science research, with many new contributions stemming from academic researchers. Yet, data controlled by platforms has become increasingly difficult for academic researchers to access. Platforms now routinely use behavior modification techniques to manipulate users' behavior, leaving academic researchers further isolated in conducting important data science and computational social science research. This isolation results from researchers' lack of access to human behavioral data, and crucially, to both the data on machine behavior that triggers and learns from the human data and the platform's behavior modification mechanisms. Given the impact of behavior modification on individual and societal well-being, we discuss the consequences for scientific knowledge creation and the roles and responsibilities of academic data scientists. Finally, we consider how current and future regulatory actions may enable academic data scientists to conduct meaningful research on platform environments in the realm of behavior modification.

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“…browsing-behaviour, voice-assistant data), claiming it would be too burdensome and/or they do not have a duty to deliver the data in question. 19 Considering the fact that these cases relate to personal data that is known to be collected by the respective companies, one may question the efficacy of using GDPR transparency measures for more exploratory purposes. Indeed, it might be hard to impossible to establish a response to an access request is (deliberately) incomplete.…”

Section: Break Through Information Monopolies (But Security Risks)mentioning

confidence: 99%