The use of data from information systems in court proceedings
This paper analyzes the challenges of using information system data as evidence in Bulgarian courts, arguing that the new regulatory framework necessitates a methodological shift from viewing evidence as isolated information units to understanding it as behavioral algorithms requiring specialized technological and analytical approaches.
Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
In the modern world, our lives leave a digital trail. Every time we send a message, make a payment, or even just walk past a sensor, information systems record the event. For a long time, the legal system treated these records like traditional paper documents: a single receipt, a single letter, or a single witness statement. If a court needed to know what happened, it looked at one piece of evidence at a time. However, as our interactions become more complex and automated, this old way of looking at things is becoming insufficient. A single log entry might show that a transaction occurred, but it cannot explain the pattern of behavior that led to it. The challenge for modern courts is no longer just about finding a piece of paper; it is about understanding the story told by thousands of digital fragments working together.
Two researchers, Dobromira Bankova and Vladimir Dimitrov, have examined how the judicial system in Bulgaria is grappling with this shift. They looked at how judges currently handle data from information systems and argued that the entire approach needs a fundamental change. Instead of treating digital records as isolated facts, the authors suggest courts must begin to see them as "behavioral algorithms." This means looking at the data not as a list of separate items, but as a map of human actions over time. By analyzing how data points connect—such as the timing of messages, the sequence of device logins, or the repetition of specific phrases—judges can reconstruct a much clearer picture of what actually happened. The researchers found that while the law is slowly catching up through new European regulations, the practical tools and training for judges and lawyers are lagging behind, creating risks for fairness in the courtroom.
To understand why this matters, one must look at how courts have traditionally worked. In the past, evidence was often viewed as a collection of individual units. A witness says they saw something, a document proves a date, or a recording captures a voice. Each piece was weighed on its own. But in the digital age, the truth often lies in the connections between pieces of data. The researchers analyzed three specific cases from recent Bulgarian court practice to illustrate this gap. In one case involving secret surveillance, the court had to decide if a written transcript of a phone call was accurate. The problem arose when the transcript was challenged. The researchers noted that simply comparing the text to the audio recording is not enough. To truly understand the context, a court needs to look at the entire history of communications: when the calls happened, who was involved, how often they spoke, and whether later conversations contradicted earlier ones. Without this broader view, a single sentence taken out of context could be misleading.
In a second case, a customer sued a bank after losing money in a sophisticated online fraud attack. The bank claimed the customer was negligent, while the customer blamed a security breach. The court did not just look at the final transaction. Instead, it examined a chain of digital events: the exact moment a mobile app was activated on a new device, the sequence of security codes sent, and the timing of the user's actions across different platforms. By treating these data points as a continuous behavioral pattern, the court could determine whether the user's actions were intentional or the result of a system failure. The researchers observed that this approach allowed the court to see the "story" of the fraud, rather than just the final result.
A third case involved a dispute over election results, where the court had to verify data from electronic voting machines. Here, the court accepted official protocols and video recordings but rejected raw data fragments from machine memory that lacked context. The decision highlighted a crucial point: digital evidence is only reliable when it is traceable and verified within a clear framework. The court refused to accept isolated bits of data that could not be linked to a specific, verified event. This reinforced the idea that data must be understood as part of a larger, coherent system to be trusted in a legal setting.
The researchers argue that a new European regulation, known as the Data Act, is beginning to provide the legal foundation for this shift. This law gives people the right to access data held by companies, which helps them build their legal cases. However, the law alone is not enough. The authors point out that the legal system is currently missing the necessary tools to handle this new type of evidence. Judges and lawyers often lack the training to understand how digital systems work, and there are no clear rules for how to present or challenge complex datasets in court. Without these safeguards, there is a risk that one side could manipulate the data by showing only a small, misleading slice of the whole picture.
The study also touches on the role of artificial intelligence in this process. As courts increasingly rely on automated systems to analyze data, the researchers warn that these systems cannot be "black boxes." If a computer program is used to interpret evidence, the court must be able to understand how it reached its conclusion. The input data, the method of analysis, and the final result must all be open to scrutiny. If the process is hidden, the right to a fair trial is compromised. The researchers emphasize that automated analysis is a tool, not a replacement for human judgment, and it must be subject to the same rigorous testing as any other form of evidence.
Ultimately, the paper concludes that the judicial system is at a turning point. The transition from looking at isolated facts to understanding behavioral patterns is not just a technical upgrade; it is a necessary evolution for justice to function in a digital society. The researchers suggest that for this to work, courts need new procedural rules, better technology, and most importantly, a workforce trained to think in terms of data patterns. They argue that without these changes, the courts will struggle to find the truth in an increasingly complex digital world. The goal is not to replace human judgment with machines, but to ensure that the tools we use to uncover the truth are as reliable and transparent as the justice system itself.
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