Trust and distrust in contradictory information transmission

We analyse the problem of contradictory information distribution in networks of agents with positive and negative trust. The networks of interest are built by ranked agents with different epistemic attitudes. In this context, positive trust is a property of the communication between agents required when message passing is executed bottom-up in the hierarchy, or as a result of a sceptic agent checking information. These two situations are associated with a confirmation procedure that has an epistemic cost. Negative trust results from refusing verification, either of contradictory information or because of a lazy attitude. We offer first a natural deduction system called SecureNDsim to model these interactions and consider some meta-theoretical properties of its derivations. We then implement it in a NetLogo simulation to test experimentally its formal properties. Our analysis concerns in particular: conditions for consensus-reaching transmissions; epistemic costs induced by confirmation and rejection operations; the influence of ranking of the initially labelled nodes on consensus and costs; complexity results

Transparency and Trust in Human-AI-Interaction: The Role of Model-Agnostic Explanations in Computer Vision-Based Decision Support

Computer Vision, and hence Artificial Intelligence-based extraction of information from images, has increasingly received attention over the last years, for instance in medical diagnostics. While the algorithms' complexity is a reason for their increased performance, it also leads to the "black box" problem, consequently decreasing trust towards AI. In this regard, "Explainable Artificial Intelligence" (XAI) allows to open that black box and to improve the degree of AI transparency. In this paper, we first discuss the theoretical impact of explainability on trust towards AI, followed by showcasing how the usage of XAI in a health-related setting can look like. More specifically, we show how XAI can be applied to understand why Computer Vision, based on deep learning, did or did not detect a disease (malaria) on image data (thin blood smear slide images). Furthermore, we investigate, how XAI can be used to compare the detection strategy of two different deep learning models often used for Computer Vision: Convolutional Neural Network and Multi-Layer Perceptron. Our empirical results show that i) the AI sometimes used questionable or irrelevant data features of an image to detect malaria (even if correctly predicted), and ii) that there may be significant discrepancies in how different deep learning models explain the same prediction. Our theoretical discussion highlights that XAI can support trust in Computer Vision systems, and AI systems in general, especially through an increased understandability and predictability

Investigation of Multiple Susceptibility Loci for Inflammatory Bowel Disease in an Italian Cohort of Patients

BACKGROUND: Recent GWAs and meta-analyses have outlined about 100 susceptibility genes/loci for inflammatory bowel diseases (IBD). In this study we aimed to investigate the influence of SNPs tagging the genes/loci PTGER4, TNFSF15, NKX2-3, ZNF365, IFNG, PTPN2, PSMG1, and HLA in a large pediatric- and adult-onset IBD Italian cohort. METHODS: Eight SNPs were assessed in 1,070 Crohn's disease (CD), 1,213 ulcerative colitis (UC), 557 of whom being diagnosed at the age of ≤16 years, and 789 healthy controls. Correlations with sub-phenotypes and major variants of NOD2 gene were investigated. RESULTS: The SNPs tagging the TNFSF15, NKX2-3, ZNF365, and PTPN2 genes were associated with CD (P values ranging from 0.037 to 7×10(-6)). The SNPs tagging the PTGER4, NKX2-3, ZNF365, IFNG, PSMG1, and HLA area were associated with UC (P values 0.047 to 4×10(-5)). In the pediatric cohort the associations of TNFSF15, NKX2-3 with CD, and PTGER4, NKX2-3, ZNF365, IFNG, PSMG1 with UC, were confirmed. Association with TNFSF15 and pediatric UC was also reported. A correlation with NKX2-3 and need for surgery (P  =  0.038), and with HLA and steroid-responsiveness (P  =  0.024) in UC patients was observed. Moreover, significant association in our CD cohort with TNFSF15 SNP and colonic involvement (P  =  0.021), and with ZNF365 and ileal location (P  =  0.024) was demonstrated. CONCLUSIONS: We confirmed in a large Italian cohort the associations with CD and UC of newly identified genes, both in adult and pediatric cohort of patients, with some influence on sub-phenotypes

Duality in Diversity: How Intrapersonal and Interpersonal Cultural Heterogeneity Relate to Firm Performance

How does cultural heterogeneity in an organization relate to its underlying capacity for execution and innovation? Cultural diversity is commonly thought to present a tradeoff between task coordination and creative problem solving, with diversity arising primarily through cultural differences between individuals. In contrast, we propose that diversity can also exist within persons when individuals hold multiple cultural beliefs about the organization. We refer to these different forms as interpersonal and intrapersonal cultural heterogeneity. We argue that the former tends to undermine coordination and portends worsening firm profitability, while the latter facilitates creativity and supports greater patenting success and more positive market valuations. To evaluate these propositions, we use computational linguistics to identify cultural content in employee reviews of nearly 500 publicly traded firms on a leading company review website and then develop novel, time-varying measures of cultural heterogeneity. Our empirical results lend support for our two core propositions, suggesting the need to rethink the performance tradeoffs of cultural heterogeneity: it may be possible to reap the creativity benefits of higher intrapersonal heterogeneity and, at the same time, the efficiency benefits of lower interpersonal heterogeneity

Duality in Diversity: How Intrapersonal and Interpersonal Cultural Heterogeneity Relate to Firm Performance

How does cultural heterogeneity in an organization relate to its underlying capacity for execution and innovation? Cultural diversity is commonly thought to present a tradeoff between task coordination and creative problem solving, with diversity arising primarily through cultural differences between individuals. In contrast, we propose that diversity can also exist within persons when individuals hold multiple cultural beliefs about the organization. We refer to these different forms as interpersonal and intrapersonal cultural heterogeneity. We argue that the former tends to undermine coordination and portends worsening firm profitability, while the latter facilitates creativity and supports greater patenting success and more positive market valuations. To evaluate these propositions, we use computational linguistics to identify cultural content in employee reviews of nearly 500 publicly traded firms on a leading company review website and then develop novel, time-varying measures of cultural heterogeneity. Our empirical results lend support for our two core propositions, suggesting the need to rethink the performance tradeoffs of cultural heterogeneity: it may be possible to reap the creativity benefits of higher intrapersonal heterogeneity and, at the same time, the efficiency benefits of lower interpersonal heterogeneity

Modelling trust in artificial agents, a first step toward the analysis of e-trust

“The original publication is available at www.springerlink.com”. Copyright Springer.This paper provides a new analysis of e-trust, trust occurring in digital contexts, among the artificial agents of a distributed artificial system. The analysis endorses a non-psychological approach and rests on a Kantian regulative ideal of a rational agent, able to choose the best option for itself, given a specific scenario and a goal to achieve. The paper first introduces e-trust describing its relevance for the contemporary society and then presents a new theoretical analysis of this phenomenon. The analysis first focuses on an agent’s trustworthiness, this one is presented as the necessary requirement for e-trust to occur. Then, a new definition of e-trust as a second-orderproperty of first-order relations is presented. It is shown that the second-orderproperty of e-trust has the effect of minimising an agent’s effort and commitment in the achievement of a given goal. On this basis, a method is provided for the objective assessment of the levels of e-trust occurring among the artificial agents of a distributed artificial system.Peer reviewe