Smart Companies: Company &amp; board members liability in the age of AI

Kindylidi, Iakovina

doi:10.21814/unio.6.1.2704

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…Starting the debate as soon as possible is a good decision but we should not try to implement solutions before they are needed, as rashness may cause a chilling effect in itself. 48…”

Section: Mandatory Insurance Schemes and Compensation Fundsmentioning

confidence: 99%

Liability and artificial intelligence in the EU: Assessing the adequacy of the current Product Liability Directive

Cabral

2020

Maastricht Journal of European and Comparative Law

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The European Union selected achieving a leadership position in the AI sector as one of the priorities for the future of the bloc as a whole. Economic reasons are behind this decision, but they are not the exclusive motive behind this objective. Undeniably, AI will have an enormous impact on world’s economy and if the EU falls behind, the standards of living that citizens of the Union currently enjoy may be at risk. Furthermore, there is also the question of keeping European values, principles and ethical standards alive in this technological transition. To achieve the leadership position it desires, it is essential for the EU to possess an updated, producer-friendly legal framework, that manages, at the same time, to ensure consumer protection and safe development of AI. One of the legal instruments that may need to be amended is the Product Liability Directive. In this paper we will study the Product Liability Directive and its shortcomings on AI regulation, along with the possible solutions to adapt the EU product liability legislation to this new technological challenge. We will assess what solutions are best suited to apply in the EU and fulfil the objective of achieving leadership in the sector.

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“…Starting the debate as soon as possible is a good decision but we should not try to implement solutions before they are needed, as rashness may cause a chilling effect in itself. 48…”

Section: Mandatory Insurance Schemes and Compensation Fundsmentioning

confidence: 99%

Liability and artificial intelligence in the EU: Assessing the adequacy of the current Product Liability Directive

Cabral

2020

Maastricht Journal of European and Comparative Law

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AI Training Datasets & Article 14 GDPR

Kindylidi¹,

Barros

2021

Rev. Dir. Est. e Telecomunicacoes

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[Purpose] At the earliest stages in AI lifecycle, training, verification and validation of machine learning and deep learning algorithm require vast datasets that usually contain personal data, which however is not obtained directly from the data subject, while very often the controller is not in a position to identify the data subjects or such identification may result to disproportionate effort. This situation raises the question on how the controller can comply with its obligation to provide information for the processing to the data subjects, especially when proving the information notice is impossible or requires a disproportionate effort. There is little to no guidance on the matter. The purpose of this paper is to address this gap by designing a clear risk-assessment methodology that can be followed by controllers when providing information to the data subjects is impossible or requires a disproportionate effort. [Methodology] After examining the scope of the transparency principle, Article 14 and its proportionality exemption in the training and verification stage of machine learning and deep learning algorithms following a doctrinal analysis, we assess whether already existing tools and methodologies can be adapted to accommodate the GDPR requirement of carrying a balancing test, in conjunction with, or independently of a DPIA. [Findings] Based on an interdisciplinary analysis, comprising theoretical and descriptive material from a legal and technological point of view, we propose a risk-assessment methodology as well as a series of risk-mitigating measures to ensure the protection of the data subject's rights and legitimate interests while fostering the uptake of the technology. [Practical Implications] The proposed balancing exercise and additional measures are designed to facilitate entities training or developing AI, especially SMEs, within and outside of the EEA, that wish to ensure and showcase the data protection compliance of their AI-based solutions.

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Smart Companies: Company & board members liability in the age of AI

Cited by 2 publications

References 4 publications

Liability and artificial intelligence in the EU: Assessing the adequacy of the current Product Liability Directive

Liability and artificial intelligence in the EU: Assessing the adequacy of the current Product Liability Directive

AI Training Datasets & Article 14 GDPR

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