Can policy making be evidence-based?

Ministers are always calling for more evidence-based interventions. Do they apply the same criterion to their own work of making policy? Perhaps surprisingly, policy making is not an evidence-free zone. However, it is important to understand the ways in which policy makers in different situations will use information differently, count different kinds of information as evidence, and so exercise different styles of judgment

Racing with or against the machine? Evidence from Europe

A fast-growing literature shows that technological change is replacing labor in routine tasks, raising concerns that labor is racing against the machine. This paper is the first to estimate the labor demand effects of routine-replacing technological change (RRTC) for Europe as a whole and at the level of 238 European regions. We develop and estimate a task framework of regional labor demand in tradable and non-tradable industries, building on Autor and Dorn (2013) and Goos et al. (2014), and distinguish the main channels through which technological change affects labor demand. These channels include the direct substitution of capital for labor in task production, but also the compensating effects operating through product demand and local demand spillovers. Our results show that RRTC has on net led to positive labor demand effects across 27 European countries over 1999-2010, indicating that labor is racing with the machine. This is not due to limited scope for human-machine substitution, but rather because sizable substitution effects have been overcompensated by product demand and its associated spillovers. However, the size of the product demand spillover – and therefore also RRTC’s total labor demand effect– depends critically on where the gains from the increased productivity of technological capital accrue

Comparative analysis of the use of AI as expert evidence

The study aims to define what artificial intelligence (AI) is and how it can be used as an expert in criminal justice. The main question of the study is what is the difference between using AI as experts in the future to give expert evidence and to assist the judge in decision-making in an adversarial system or in an inquisitorial system? The study, which is based on a comparative analysis of evidence systems, also aims to compare human experts with AI experts. The study considers situations in which AI could be used to give evidence in court, and raises the following key questions on the subject. It discusses the relevance and admissibility of expert evidence and whether there is a level of certainty to accept, for example, the AI expert’s opinion as always true. In different legal systems, the process of adapting artificial evidence as expert testimony is different, and therefore different legal adaptations are needed, coupled with different directions of extensive research and development. AI can only provide its expert opinion based on the data stored in its algorithms. Lack of input means lack of experience in interpreting and evaluating data. The main result of the comparative analysis is that if we consider AI as an expert in an adversarial or inquisitorial, or even mixed, system, the aim should not be to replace human expertise, but to allow AI and human experts to coexist, and eventually to identify the domains in which AI could be developed and used more than in others. Dactyloscopy, image identification, graphology are typical areas where AI is being used successfully and further reinforcement is welcome. The study also highlights the use of AI in the legal profession in general and the issues surrounding the use of AI as a human expert witness

the admissibility of AI- generated evidence

Durante as duas últimas décadas, a Inteligência Artificial tornou-se uma presença constante nas nossas vidas. Ao impactar setores relevantes da sociedade, tem relevando o seu caráter disruptivo, sendo um dos motores impulsionadores da Quarta Revolução Industrial. A Inteligência Artificial além dos seus presentes benefícios para a humanidade, promete soluções inovadoras para os problemas que afligem a sociedade contemporânea, porém a mesma comporta uma duplicidade de efeitos. Os sistemas de Inteligência Artificial pela sua capacidade de monitorizar o seu ambiente circundante, e autonomamente recolher, processar dados, aprender e agir, podem concretizar riscos para os direitos fundamentais, principalmente no contexto da justiça criminal. Esta análise irá focar-se nas especificidades dos sistemas dotados de Inteligência Artificial, aprofundando a temática da admissibilidade da prova gerada por Inteligência Artificial no quadro probatório do Direito Processual Penal Português à luz dos direitos de defesa do arguido e dos seus princípios que norteadores.During the last two decades Artificial Intelligence became ubiquitous in our lives. Revealing itself as a disruptive technology, it is already impacting important sectors of society, being a driver of the Fourth Industrial Revolution. Artificial Intelligence is benefiting humanity, and promises innovative solutions to modern-life problems, nevertheless it has a twofold effect. Artificial Intelligence as systems that are capable to monitor their surrounding environment, autonomously collect and process data, learn and act, may constitute harm to fundamental rights, mainly when deployed to criminal justice. This analysis will focus on the specificities of Artificial Intelligence systems, delving into the admissibility of AI-generated evidence in the Portuguese criminal evidentiary framework in light of the defence rights and structuring principles of Portuguese criminal procedure