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Maastricht University (UM)
Are you interested in criminal law and the intersection between liability and technology? Do you want to be part of a research team that is exploring the boundaries of criminal law and investigating how new advancements in Artificial Intelligence are reshaping the landscape of accountability? If so, apply to this PhD position and join us at the Department of Criminal Law and Criminology at Maastricht University.
Job Description
Research project: Adjudicating Criminal Liability in Multifactorial Technological Scenarios.
Over the past 50 years, our society (and our legal systems) has ceased to view disasters as “acts of fate” to be dealt with only after their occurrence. In this day and age, catastrophes are seen as a phenomenon to be prevented. It follows that when things go wrong, and disasters occur, someone must be held accountable. The undesired event which results from a failure of such systems, i.e., a catastrophe, is of a multifactorial nature: it can be caused by a combination of natural and technological factors, such as omissive conducts of multiple subjects, decisions taken in split-second scenarios, structural deficiencies of the system, and, in some cases, even by the conduct of the victims themselves. It follows that ascribing the fault of an accident to a single “root cause” (as it is in the case of criminal proceedings) appears to be an inherently flawed process.
The recent evolution in the field of Artificial Intelligence (AI) has led to introduction of AI-based safety enhancing features and accident prevention systems. These systems can have different duties, such as observing and assessing a person’s fitness to perform a specific high-risk task and issuing warnings/take-over requests. The introduction of these systems leads to the emergence of cooperative actions between the AI system and the human agent, which, again, leads to shared responsibility. This might have relevant consequences on the attribution of criminal liability. On the one hand, there might be the need pose new questions and, on the other hand, to evaluate the need for new answers to old questions.
Moreover, the same evaluations will then enter the criminal trial and may be used as evidence against the defendant. Rules of criminal procedure might not be equipped to deal with this new type of evidence. Differently from other types of “traditional evidence”, establishing reliability, accuracy, and credibility of AI-evidence could be challenging due to its characteristics, such as its opaque nature. One could also question its relevance and probative value. These aspects impact questions of admissibility in court. Other relevant issues include the fact that AI systems cannot be questioned – at least not in the same ways as humans can – even by those who created them (black box issue); and the risk of imposing an unfair burden on the defendant, who usually is in a position of economical inferiority in comparison to the prosecution and lacks access to the tools to challenge the AI-based evidence.
In order to address these questions, two streams of research have been identified:
The candidate is expected to present an original research project that fits into one of the two research streams identified above. Please note that the questions provided are prompts to help the candidate develop their own research question and are not exhaustive.
The supervisory team will be composed of dr. Alice Giannini and prof. dr. André Klip .
The candidate will:
Requirements
We are seeking a highly motivated candidate with a completed university master’s degree (or research master) in Law – preferably with a specialization in criminal and criminal procedural law, criminology or other discipline relevant for this PhD position.
Moreover, the ideal candidate should possess the following skills:
What we offer
As a PhD at the Faculty of Law , you will be employed by the most international university in the Netherlands, located in the beautiful city of Maastricht. In addition, we offer you:
The terms of employment at Maastricht University are largely set out in the collective labor agreement of Dutch Universities. In addition, local provisions specific to UM apply.