Cognitive Bias, Privacy Rights, and Digital Evidence in International Criminal Proceedings: Demystifying the Double-Edged AI Revolution

Riccardo Vecellio Segate

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

Abstract

International criminal tribunals (icts) have found, almost consistently, that unlawfully and/or secretly obtained evidence is admissible. De facto, defendants in international criminal law (icl) enjoy no privacy-related procedural safeguards under either the applicable domestic law or international human rights law (ihrl). Privacy violations are not confined to those impairing defendants’ rights; they might result in premature acquittals or in misconducts vis-à-vis the victims, too. While this is practically unescapable a compromise due to the ‘high profile’ of the accused and the complexity, length, momentousness, and ‘political charge’ of these trials, over-relaxed admissibility rules become unsustainable as far as digital evidence is concerned, in that they add to the latter’s inherently low reliability and heavy cognitive impact. Facing this issue, it is legit to wonder whether artificial intelligence (ai) might mitigate privacy violations or render them no longer necessary, thus improving the fairness record of the International Criminal Court (icc) and other icts.

Original languageEnglish
Pages (from-to)242-279
Number of pages38
JournalInternational Criminal Law Review
Volume21
Issue number2
DOIs
Publication statusPublished - 10 Mar 2021

Keywords

  • Admissibility
  • Algorithms
  • Artificial intelligence
  • Cognitive bias
  • Digital evidence
  • Exclusionary rules
  • Fair trial
  • International Criminal Court
  • Machine learning
  • Probative weight
  • Prosecutorial secrecy
  • Right to privacy

ASJC Scopus subject areas

  • Sociology and Political Science
  • Political Science and International Relations
  • Law

Fingerprint

Dive into the research topics of 'Cognitive Bias, Privacy Rights, and Digital Evidence in International Criminal Proceedings: Demystifying the Double-Edged AI Revolution'. Together they form a unique fingerprint.

Cite this