A hundred years ago it was bumps on the head… (Phrenology)
The Criminality From Face Illusion
The automatic analysis of face images can generate predictions about a person's gender, age, race, facial expression, body mass index, and various other indices and conditions. A few recent publications have claimed success in analyzing an image of a person's face in order to predict the person's status as Criminal / Non-Criminal. Predicting criminality from face may initially seem similar to other facial analytics, but we argue that attempts to create a criminality-from-face algorithm are necessarily doomed to fail, that apparently promising experimental results in recent publications are an illusion resulting from inadequate experimental design, and that there is potentially a large social cost to belief in the criminality from face illusion.
“That AI done me wrong!”
Liability of artificial intelligence as a subject of legal relations
This article is concerned with a burning issue, namely, liability for offenses committed with the use of artificial intelligence and methods of compensating the damage caused by such illegal actions. The study aims at analyzing several legal acts that regulate the possible application of A.I., reveal problems in this field and suggest possible solutions.
The authors of the article use theoretical and general philosophical methods of cognition, as well as traditional legal methods. The main method is analogy that highlights the need to eliminate gaps in the current Russian legislation. Based on the concepts of A.I. formed by scholars from different countries and using the method of comparative analysis, the authors attempt to consider offenses committed with the use of A.I. in the territory of Russia.
To determine A.I. as a subject of legal relations, different scholars developed original concepts. The authors of the article have studied some hypotheses regarding the development of technologies that increase the interaction between people and computers and its possible danger since it might blur the borders between A.I. and its operators.
The study results can be useful for the theory of civil and administrative law in determining the person responsible for the harm caused by A.I. and for the application of liability rules in relation to a new road user. Such conclusions might be of interest to the legislator to fill in the gaps in the legal regulation of compensation for the harm caused by A.I.
The authors are the first to draw a certain parallel between the sources of administrative and civil law regarding legal liability for the commission of an offense and compensation for the damage caused by A.I. In addition, they have analyzed the current legislation of the Russian Federation governing liability for the violation of traffic rules.
Toward an AI judge?
AI-lead Court Debate Case Investigation
The multi-role judicial debate composed of the plaintiff, defendant, and judge is an important part of the judicial trial. Different from other types of dialogue, questions are raised by the judge, The plaintiff, plaintiff's agent defendant, and defendant's agent would be to debating so that the trial can proceed in an orderly manner. Question generation is an important task in Natural Language Generation. In the judicial trial, it can help the judge raise efficient questions so that the judge has a clearer understanding of the case. In this work, we propose an innovative end-to-end question generation model-Trial Brain Model (TBM) to build a Trial Brain, it can generate the questions the judge wants to ask through the historical dialogue between the plaintiff and the defendant. Unlike prior efforts in natural language generation, our model can learn the judge's questioning intention through predefined knowledge. We do experiments on real-world datasets, the experimental results show that our model can provide a more accurate question in the multi-role court debate scene.
If this is difficult, think how much worse AI will be.
Software must be recognised as an important output of scholarly research
Software now lies at the heart of scholarly research. Here we argue that as well as being important from a methodological perspective, software should, in many instances, be recognised as an output of research, equivalent to an academic paper. The article discusses the different roles that software may play in research and highlights the relationship between software and research sustainability and reproducibility. It describes the challenges associated with the processes of citing and reviewing software, which differ from those used for papers. We conclude that whilst software outputs do not necessarily fit comfortably within the current publication model, there is a great deal of positive work underway that is likely to make an impact in addressing this.
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