Artificial Intelligence, Computational Modelling and Criminal Proceedings

Quattrocolo, Serena

doi:10.1007/978-3-030-52470-8

Cited by 23 publications

(6 citation statements)

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“…The long-standing practice of multilingual communication confirms that the translation and interpreting activities play a crucial role major societal contexts and settings (Atabekova, 2020) Academia has paid consistent attention to the issues and challenges that emerge in the course of interpreter's engagement in the criminal proceedings. Scholars explore the topic within the various domains including interpreter's training and legal grounds, consider the point within the issues of justice provision (Atabekova, 2016;Biel, 2011;Elias-Bursać, Askew, 2018;Lee, 2017), and ICT use to enhance the quality of service provision (Atabekova, 2018;Orozco Jutorán, 2018;Quattrocolo, 2020). In Russia a number of offences are committed by people who do not have knowledge of the Russian language and this fact has reaffirmed the topicality of this article.…”

Section: Introductionmentioning

confidence: 74%

Problematic Aspects of the Interpreter's Participation in Criminal Proceedings

Nozdracheva¹

2021

Proceedings of INTCESS 2021- 8th International Conference on Education and Education of Social Sciences

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This article is devoted to the key problems which interpreters face when they participate in criminal proceedings. The paper also accumulates the opinion of legal experts on the topic under study. Respective problematic aspects have been identified by Russian and foreign researchers and practitioners who deal with the issue in practice, in criminal settings, and in the training fields, as well.The article deals with organizational and procedural issues related to an interpreter`s participation in criminal proceedings, interpreter`s competence identification, possible unforeseeable errors which may arise in the course of interpreting.The methodology combined theoretical and empirical studies, aggregated data from academic findings, analysis of some cases, information based on the activities of institutions which operate as linguistic and judicial expertise units, data received from specialists engaged in education policy. The paper also used the background provisions of the Code of Criminal Procedure of the Russian Federation which relate to the translator and interpreter's status.The paper consistently explores the components of interpreter's competence that are mandatory for his/her efficient work in court within the broader context of the overall interpreter's work within the criminal settings. Interpreters' extralinguistic capacities and personal features are also subject to the investigation. Further the interpreter's impartiality, rights with regard to the participation in the proceedings draws the audience attention, as well. Some other extralinguistic points are in the focus of consideration, as well.The findings have made it possible to identify some challenging points that refer procedural, recruiting, and qualification issues with regard to the interpreter's engagement in the criminal proceedings in Russia.

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Section: Introductionmentioning

confidence: 74%

Problematic Aspects of the Interpreter's Participation in Criminal Proceedings

Nozdracheva¹

2021

Proceedings of INTCESS 2021- 8th International Conference on Education and Education of Social Sciences

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“…These drivers of an AI for recidivism rate assessment may be the inner opacity of the system, its reliability, the poor quality or misuse of the training data (e.g., outdated or incomplete data sets), and its validity. Validity is critical to ensure that the instrument measures what it is intended to measure (Quattrocolo, 2020). When these hazard drivers compound, they can lead to the AIs perpetrating discrimination biases.…”

Section: An Illustration Case For Showing the Contributions Of The Se...mentioning

confidence: 99%

AI Risk Assessment: A Scenario-Based, Proportional Methodology for the AI Act

Novelli,

Casolari,

Rotolo

et al. 2024

DISO

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The EU Artificial Intelligence Act (AIA) defines four risk categories for AI systems: unacceptable, high, limited, and minimal. However, it lacks a clear methodology for the assessment of these risks in concrete situations. Risks are broadly categorized based on the application areas of AI systems and ambiguous risk factors. This paper suggests a methodology for assessing AI risk magnitudes, focusing on the construction of real-world risk scenarios. To this scope, we propose to integrate the AIA with a framework developed by the Intergovernmental Panel on Climate Change (IPCC) reports and related literature. This approach enables a nuanced analysis of AI risk by exploring the interplay between (a) risk determinants, (b) individual drivers of determinants, and (c) multiple risk types. We further refine the proposed methodology by applying a proportionality test to balance the competing values involved in AI risk assessment. Finally, we present three uses of this approach under the AIA: to implement the Regulation, to assess the significance of risks, and to develop internal risk management systems for AI deployers.

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“…Perhaps more importantly, as a whole, the intercept evidence tells the story of the VRS military participation in the attack on Srebrenica and the events that follow, and forms an important part of the mosaic of evidence to be introduced by the Prosecution". 10 In Popović, intercepted communications were used to demonstrate the chain of command and provided a narrative of the VRS attack on Srebrenica and the events that followed. 11 Telecommunications evidence, including call data records and cell site information, were presented before the Special Tribunal of Lebanon (STL), the sole international court to have jurisdiction over the crime of terrorism, to prove the preparatory acts leading up to the terrorist attack which killed the Prime Minister of Lebanon, Rafiq Hariri on 14 February 2005.…”

Section: The Increasing Use Of Digital Evidence In International Crim...mentioning

confidence: 99%

Law in the Age of Modern Technologies

2023

EU and Comparative Law Issues and Challenges Series

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Artificial Intelligence, Computational Modelling and Criminal Proceedings

Cited by 23 publications

References 0 publications

Problematic Aspects of the Interpreter's Participation in Criminal Proceedings

Problematic Aspects of the Interpreter's Participation in Criminal Proceedings

AI Risk Assessment: A Scenario-Based, Proportional Methodology for the AI Act

Law in the Age of Modern Technologies

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