A Controller Without Control. Embedded Artificial Intelligence – A Catalyst to Reconsider the Controller/Processor Relationship of the GDPR

Publikation: Bidrag til bog/antologi/rapportBidrag til bog/antologiForskningfagfællebedømt

Standard

A Controller Without Control. Embedded Artificial Intelligence – A Catalyst to Reconsider the Controller/Processor Relationship of the GDPR. / Dahi, Alan; Corrales Compagnucci, Marcelo.

AI in eHealth: Human Autonomy, Data Governance & Privacy in Healthcare. red. / Marcelo Corrales Compagnucci; Michael L. Wilson; Mark Fenwick; Nikolaus Forgó; Till Bärnighausen. Cambridge : Cambridge University Press, 2021. (Cambridge Bioethics and Law ).

Publikation: Bidrag til bog/antologi/rapportBidrag til bog/antologiForskningfagfællebedømt

Harvard

Dahi, A & Corrales Compagnucci, M 2021, A Controller Without Control. Embedded Artificial Intelligence – A Catalyst to Reconsider the Controller/Processor Relationship of the GDPR. i M Corrales Compagnucci, M L. Wilson, M Fenwick, N Forgó & T Bärnighausen (red), AI in eHealth: Human Autonomy, Data Governance & Privacy in Healthcare. Cambridge University Press, Cambridge, Cambridge Bioethics and Law .

APA

Dahi, A., & Corrales Compagnucci, M. (Accepteret/In press). A Controller Without Control. Embedded Artificial Intelligence – A Catalyst to Reconsider the Controller/Processor Relationship of the GDPR. I M. Corrales Compagnucci, M. L. Wilson, M. Fenwick, N. Forgó, & T. Bärnighausen (red.), AI in eHealth: Human Autonomy, Data Governance & Privacy in Healthcare Cambridge: Cambridge University Press. Cambridge Bioethics and Law

Vancouver

Dahi A, Corrales Compagnucci M. A Controller Without Control. Embedded Artificial Intelligence – A Catalyst to Reconsider the Controller/Processor Relationship of the GDPR. I Corrales Compagnucci M, L. Wilson M, Fenwick M, Forgó N, Bärnighausen T, red., AI in eHealth: Human Autonomy, Data Governance & Privacy in Healthcare. Cambridge: Cambridge University Press. 2021. (Cambridge Bioethics and Law ).

Author

Dahi, Alan ; Corrales Compagnucci, Marcelo. / A Controller Without Control. Embedded Artificial Intelligence – A Catalyst to Reconsider the Controller/Processor Relationship of the GDPR. AI in eHealth: Human Autonomy, Data Governance & Privacy in Healthcare. red. / Marcelo Corrales Compagnucci ; Michael L. Wilson ; Mark Fenwick ; Nikolaus Forgó ; Till Bärnighausen. Cambridge : Cambridge University Press, 2021. (Cambridge Bioethics and Law ).

Bibtex

@inbook{be90ed76c7ee4430ba420bd6fc8d657d,
title = "A Controller Without Control.: Embedded Artificial Intelligence – A Catalyst to Reconsider the Controller/Processor Relationship of the GDPR",
abstract = "In the past, AI-devices offloaded their processing to the cloud, clearly implicating the provider of the cloud as either a controller or a processor under the GDPR. Increasingly, however, AI-driven processing is moving away from the cloud. Dedicated AI chipsets embedded in mobile clients and various edge devices now provide on-device predictions. A smart phone can screen for skin melanomas without sending any data to the cloud or app developer, and a bedside patient monitoring system can process locally in the hospital without sending any personal data to the device manufacturer. Such localized processing reveals underlying problems of how responsibility within data protection is allocated. For example, device manufacturers are typically deemed to fall outside the scope of the GDPR. This chapter argues that the current understanding of the controller/processor framework is too narrow. This is demonstrated through various processing scenarios.",
author = "Alan Dahi and {Corrales Compagnucci}, Marcelo",
year = "2021",
language = "English",
series = "Cambridge Bioethics and Law",
editor = "{Corrales Compagnucci}, {Marcelo } and {L. Wilson}, {Michael } and Mark Fenwick and Nikolaus Forg{\'o} and Till Bärnighausen",
booktitle = "AI in eHealth",
publisher = "Cambridge University Press",
address = "United Kingdom",

}

RIS

TY - CHAP

T1 - A Controller Without Control.

T2 - Embedded Artificial Intelligence – A Catalyst to Reconsider the Controller/Processor Relationship of the GDPR

AU - Dahi, Alan

AU - Corrales Compagnucci, Marcelo

PY - 2021

Y1 - 2021

N2 - In the past, AI-devices offloaded their processing to the cloud, clearly implicating the provider of the cloud as either a controller or a processor under the GDPR. Increasingly, however, AI-driven processing is moving away from the cloud. Dedicated AI chipsets embedded in mobile clients and various edge devices now provide on-device predictions. A smart phone can screen for skin melanomas without sending any data to the cloud or app developer, and a bedside patient monitoring system can process locally in the hospital without sending any personal data to the device manufacturer. Such localized processing reveals underlying problems of how responsibility within data protection is allocated. For example, device manufacturers are typically deemed to fall outside the scope of the GDPR. This chapter argues that the current understanding of the controller/processor framework is too narrow. This is demonstrated through various processing scenarios.

AB - In the past, AI-devices offloaded their processing to the cloud, clearly implicating the provider of the cloud as either a controller or a processor under the GDPR. Increasingly, however, AI-driven processing is moving away from the cloud. Dedicated AI chipsets embedded in mobile clients and various edge devices now provide on-device predictions. A smart phone can screen for skin melanomas without sending any data to the cloud or app developer, and a bedside patient monitoring system can process locally in the hospital without sending any personal data to the device manufacturer. Such localized processing reveals underlying problems of how responsibility within data protection is allocated. For example, device manufacturers are typically deemed to fall outside the scope of the GDPR. This chapter argues that the current understanding of the controller/processor framework is too narrow. This is demonstrated through various processing scenarios.

M3 - Book chapter

T3 - Cambridge Bioethics and Law

BT - AI in eHealth

A2 - Corrales Compagnucci, Marcelo

A2 - L. Wilson, Michael

A2 - Fenwick, Mark

A2 - Forgó, Nikolaus

A2 - Bärnighausen, Till

PB - Cambridge University Press

CY - Cambridge

ER -

ID: 241213981