Robots and AI as Legal Subjects? Disentangling the Ontological and Functional Perspective

: Robotics and AI-based applications (RAI) are often said to be so technologically advanced that they should be held responsible for their actions, instead of the human who designs or operates them. The paper aims to prove that this thesis ("the exceptionalist claim")-as it stands-is both theoretically incorrect and practically inadequate. Indeed, the paper argues that such claim is based on a series of misunderstanding over the very notion and functions of "legal responsibility", which it then seeks to clarify by developing and interdisciplinary conceptual taxonomy. In doing so, it aims to set the premises for a more constructive debate over the feasibility of granting legal standing to robotic application. After a short Introduction setting the stage of the debate, the paper addresses the ontological claim, distinguishing the philosophical from the legal debate on the notion of i) subjectivity and ii) agency, with their respective implications. The analysis allows us to conclude that the attribution of legal subjectivity and agency are purely fictional and technical solutions to facilitate legal interactions, and is not dependent upon the intrinsic nature of the RAI. A similar structure is maintained with respect to the notion of responsibility, addressed first in a philosophical and then legal perspective, to demonstrate how the latter is often utilized to both pursue ex ante deterrence and ex post compensation. The focus on the second objective allows us to bridge the analysis towards functional (law and economics based) considerations, to discuss how even the attribution of legal personhood may be conceived as an attempt to simplify certain legal interactions and relations. Within such a framework, the discussion whether to attribute legal subjectivity to the machine needs to be kept entirely within the legal domain, and grounded on technical (legal) considerations, to be argued on a functional, bottom-up analysis of specific classes of RAI. That does not entail the attribution of animacy or the ascription of a moral status to the entity itself

The Expert Group’s Report on Liability for Artificial Intelligence and Other Emerging Digital Technologies: a critical assessment

This article offers a critical discussion of the “Report on Liability for Artificial Intelligence and Other Emerging Digital Technologies” released by the Expert Group on Liability and New Technologies. In particular, the authors consider: the excessive diversity of applications encompassed through the notion of “artificial intelligence and other emerging technologies”; the distinction between high- and low-risk applications as a potential source of legal uncertainty; the primary reliance on evidentiary rules over substantive ones; the problematic role attributed to safety rules; the unclear relationship between the Product Liability Directive and other ad hoc liability regimes; the radical exclusion of electronic personhood as a way of addressing liability issues; and the limited contextualisation of compulsory insurance and no-compensation funds

A Glimpse into the Effects of Climate Adaptation on Shaping the Goat Genome

The goat is one of the most adaptable livestock species, present worldwide in many different environments. The ADAPTMAP consortium collected DNA from goats worldwide to investigate the genetic basis of adaptation to these environments. The major findings were that animals in the Tropical areas had genetic differences likely associated with genes that influence the size (smaller animals), while in the other environments, different forms of the same gene were seen in different environments suggesting natural or artificial selection

Genome-wide association studies of inflammatory bowel disease in German shepherd dogs

Canine Inflammatory Bowel Disease (IBD) is considered a multifactorial disease caused by complex interactions between the intestinal immune system, intestinal microbiota and environmental factors in genetically susceptible individuals. Although IBD can affect any breed, German shepherd dogs (GSD) in the UK are at increased risk of developing the disease. Based on previous evidence, the aim of the present study was to identify single nucleotide polymorphisms (SNPs), which may confer genetic susceptibility or resistance to IBD using a genome-wide association study (GWAS). Genomic DNA was extracted from EDTA blood or saliva samples of 96 cases and 98 controls. Genotyping of cases and controls was performed on the Canine Illumina HD SNP array and data generated was analyzed using PLINK. Several SNPs and regions on chromosomes 7,9,11 and 13 were detected to be associated with IBD using different SNP-by-SNP association methods and FST windows approach. Searching one Mb up-and down-stream of the most significant SNPs, as identified by single SNP analysis as well as 200Kb before and after the start and the end position of the associated regions identified by FST windows approach, we identified 63 genes. Using a combination of pathways analysis and a list of genes that have been reported to be involved in human IBD, we identified 16 candidate genes potentially associated with IBD in GSD

Studio di Geni candidati per caratteristiche produttive e della carcassa nel suino pesante italiano. Identificazione di nuovi Marcatori Molecolari, studi di espressione ed analisi di associazione utilizzando differenti disegni sperimentali

Heavy pig breeding in Italy is mainly oriented for the production of high quality processed products. Of particular importance is the dry cured ham production, which is strictly regulated and requires specific carcass characteristics correlated with green leg characteristics. Furthermore, as pigs are slaughtered at about 160 kg live weight, the Italian pig breeding sector faces severe problems of production efficiency that are related to all biological aspects linked to growth, feed conversion, fat deposition and so on. It is well known that production and carcass traits are in part genetically determined. Therefore, as a first step to understand genetic basis of traits that could have a direct or indirect impact on dry cured ham production, a candidate gene approach can be used to identify DNA markers associated with parameters of economic importance. In this thesis, we investigated three candidate genes for carcass and production traits (TRIB3, PCSK1, MUC4) in pig breeds used for dry cured ham production, using different experimental approaches in order to find molecular markers associated with these parameters.L’allevamento del suino pesante italiano è principalmente orientato verso la produzione di prodotti stagionati di alto pregio. Particolarmente importante è la produzione del prosciutto crudo, che è strettamente regolata e richiede specifiche caratteristiche della carcassa correlate con le caratteristiche della coscia fresca. Inoltre dato che i suini vengono macellati ad un peso di circa 160kg, il settore dell’allevamento del suino pesante italiano si trova a dover far fronte a numerosi problemi di efficienza di produzione che sono correlati a tutti gli aspetti biologici legati a crescita, conversione alimentare, deposizione di grasso e così via. E’ ben noto che caratteri produttivi e caratteristiche della carcassa sono in parte geneticamente determinate. Perciò come primo step per comprendere le basi genetiche di attributi che possono avere un impatto diretto o indiretto nella produzione del prosciutto crudo, l’approccio del gene candidato può essere usato per identificare marcatori a DNA associati a caratteri di importanza economica. In questa tesi abbiamo investigato tre geni candidati per caratteri produttivi e relativi alla carcassa (TRIB3, PCSK1, MUC4)in razze suine usate per la produzione del prosciutto crudo, utilizzando differenti approcci sperimentali al fine di trovare marcatori molecolari associati con questi caratteri

Footprints of Natural Selection in North Atlantic Eels: A Review

The study of natural selection and local adaptation is a thriving field of research. Local adaptation is driven by environment components and results in locally adapted phenotypes with higher fitness relative to other phenotypes from other locations in the species range. Tests of local adaptations have traditionally been done using transplant experiments, but the advent of next-generation sequencing methods have allowed the study of local adaptation to move from a phenotypic to a genomic approach. By using genome scans and state-of-the-art statistical tests, researchers can identify genes putatively under selection and study the genomic architecture of local adaptation, which often includes the observation of clustering of adaptive genes concentrated in fewer genomic regions known as “genomic islands of divergence”. The two species of North Atlantic eels, the European and the American eel, are excellent species for studying selection since they are panmictic and present large population sizes, show a wide distribution range across extremely heterogenous environments, and are subject to high mortalities. We reviewed studies of natural selection and local adaptation in American eel, European eel, between life cycle stages, between European and American eel. Finally, we discussed genome architecture in relation to local adaptation in eels and the role of both genetic (i.e., local adaptation) and non-genetic (i.e., phenotypic plasticity) in the survival of eels across their distribution range

Blood-based gene expression as non-lethal tool for inferring salinity-habitat history of European eel (Anguilla anguilla)

The European eel is a facultative catadromous species, meaning that it can skip the freshwater phase or move between marine and freshwater habitats during its continental life stage. Otolith microchemistry, used to determine the habitat use of eel or its salinity history, requires the sacrifice of animals. In this context, blood-based gene expression may represent a non-lethal alternative. In this work, we tested the ability of blood transcriptional profiling to identify the different salinity-habitat histories of European eel. Eels collected from different locations in Norway were classified through otolith microchemistry as freshwater residents (FWR), seawater residents (SWR) or inter-habitat shifters (IHS). We detected 3451 differentially expressed genes from blood by comparing FWR and SWR groups, and then used that subset of genes in a machine learning approach (i.e., random forest) to the extended FWR, SWR, and IHS group. Random forest correctly classified 100% of FWR and SWR and 83% of the IHS using a minimum of 30 genes. The implementation of this non-lethal approach may replace otolith-based microchemistry analysis for the general assessment of life-history tactics in European eels. Overall, this approach is promising for the replacement or reduction of other lethal analyses in determining certain fish traits.publishedVersio