Inference Rules in Nelson’s Logics, Admissibility and Weak Admissibility

© 2015, Springer Basel. Our paper aims to investigate inference rules for Nelson’s logics and to discuss possible ways to determine admissibility of inference rules in such logics. We will use the technique offered originally for intuitionistic logic and paraconsistent minimal Johannson’s logic. However, the adaptation is not an easy and evident task since Nelson’s logics do not enjoy replacement of equivalences rule. Therefore we consider and compare standard admissibility and weak admissibility. Our paper founds algorithms for recognizing weak admissibility and admissibility itself – for restricted cases, to show the problems arising in the course of study

To trust or not to trust? An assessment of trust in AI-based systems: Concerns, ethics and contexts

Artificial intelligence (AI) characterizes a new generation of technologies capable of interacting with the environment and aiming to simulate human intelligence. The success of integrating AI into organizations critically depends on workers' trust in AI technology. Trust is a central component of the interaction between people and AI, as incorrect levels of trust may cause misuse, abuse or disuse of the technology. The European Commission's High-level Expert Group on AI (HLEG) have adopted the position that we should establish a relationship of trust with AI and should cultivate trustworthy AI. This article investigates the links between trust in AI, concerns related to AI use, and the ethics related to such use. We used data collected in 2019 from more than 30,000 individuals across the EU28. The data focuses on living conditions, trust, and AI uses and concerns. An econometric model is used. The endogenous variable is an ordered measure of trust in AI. We use an ordered logit model to highlight the factors associated with an increased level of trust in AI in Europe. The results show that many concerns related to AI use are linked to AI trust, and the ability to try out AI applications will also have an impact on initial trust. To enhance trust, practitioners can try to maximize the technological features in AI systems. The representation of the AI as a humanoid or a loyal pet (e.g., a dog) will facilitate initial trust formation. Moreover, findings reveal an unequal degree of trust in AI across countries

To trust or not to trust? An assessment of trust in AI-based systems: Concerns, ethics and contexts

Artificial intelligence (AI) characterizes a new generation of technologies capable of interacting with the environment and aiming to simulate human intelligence. The success of integrating AI into organizations critically depends on workers' trust in AI technology. Trust is a central component of the interaction between people and AI, as incorrect levels of trust may cause misuse, abuse or disuse of the technology. The European Commission's High-level Expert Group on AI (HLEG) have adopted the position that we should establish a relationship of trust with AI and should cultivate trustworthy AI. This article investigates the links between trust in AI, concerns related to AI use, and the ethics related to such use. We used data collected in 2019 from more than 30,000 individuals across the EU28. The data focuses on living conditions, trust, and AI uses and concerns. An econometric model is used. The endogenous variable is an ordered measure of trust in AI. We use an ordered logit model to highlight the factors associated with an increased level of trust in AI in Europe. The results show that many concerns related to AI use are linked to AI trust, and the ability to try out AI applications will also have an impact on initial trust. To enhance trust, practitioners can try to maximize the technological features in AI systems. The representation of the AI as a humanoid or a loyal pet (e.g., a dog) will facilitate initial trust formation. Moreover, findings reveal an unequal degree of trust in AI across countries

3D additive-manufactured nanocomposite magnetic scaffolds: Effect of the application mode of a time-dependent magnetic field on hMSCs behavior

Over the past few years, the influence of static or dynamic magnetic fields on biological systems has become a topic of considerable interest. Magnetism has recently been implicated to play significant roles in the regulation of cell responses and, for this reason, it is revolutionizing many aspects of healthcare, also suggesting new opportunities in tissue engineering. The aim of the present study was to analyze the effect of the application mode of a time-dependent magnetic field on the behavior of human mesenchymal stem cells (hMSCs) seeded on 3D additive-manufactured poly(ɛ-caprolactone)/iron-doped hydroxyapatite (PCL/FeHA) nanocomposite scaffolds