The case arose from a German labour dispute where an employer accessed a former worker’s eBay account to prove alleged misconduct. The national court asked the CJEU whether evidence gathered unlawfully could still be lawfully processed in judicial proceedings.
The Advocate General stated that GDPR principles, including storage limitation and lawfulness, apply equally to courts. Yet no absolute ban prevents judges from handling unlawfully obtained data if national law provides safeguards consistent with the EU rights.
EU law leaves rules on evidence admissibility to member states, provided fairness, proportionality, and necessity are respected. The opinion emphasises that courts must balance privacy rights with their duty to determine the truth.
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A newly proposed rule by the Federal Judicial Conference could reshape how AI-generated evidence is treated in court. Dubbed Rule 707, it would allow such machine-generated evidence to be admitted only if it meets the same reliability standards required of expert testimony under Rule 702.
However, it would not apply to outputs from simple scientific instruments or widely used commercial software. The rule aims to address concerns about the reliability and transparency of AI-driven analysis, especially when used without a supporting expert witness.
Critics argue that the limitation to non-expert presentation renders the rule overly narrow, as the underlying risks of bias and interpretability persist regardless of whether an expert is involved. They suggest that all machine-generated evidence in US courts should be subject to robust scrutiny.
The Advisory Committee is also considering the scope of terminology such as ‘machine learning’ to prevent Rule 707 from encompassing more than intended. Meanwhile, a separate proposed rule regarding deepfakes has been shelved because courts already have tools to address the forgery.
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Two Spanish scientists question the thesis of ‘two Ukraine’: pro-West or pro-Russian by analysing a data set on violent events in Ukraine since January 2021.
The analysis shows that conflicts can arise from many factors beyond simple East-West binary optics and the solution is not to split Ukraine in two.
According to the authors, lack of data is the greatest problem in this scientific method.
As opposed to other fields, like engineering, obtaining reliable and high-quality data about social and political events is a major challenge.
The greatest challenge to using statistical models and scientific methods in diplomacy will be finding timely, reliable, and usable data.
