Mandevillian Intelligence: From Individual Vice to Collective Virtue

Abstract Mandevillian intelligence is a specific form of collective intelligence in which individual cognitive vices (i.e., shortcomings, limitations, constraints and biases) are seen to play a positive functional role in yielding collective forms of cognitive success. In this talk, I will introduce the concept of mandevillian intelligence and review a number of strands of empirical research that help to shed light on the phenomenon. I will also attempt to highlight the value of the concept of mandevillian intelligence from a philosophical, scientific and engineering perspective. Inasmuch as we accept the notion of mandevillian intelligence, then it seems that the cognitive and epistemic value of a specific social or technological intervention will vary according to whether our attention is focused at the individual or collective level of analysis. This has a number of important implications for how we think about the cognitive impacts of a number of Web-based technologies (e.g., personalized search mechanisms). It also forces us to take seriously the idea that the exploitation (or even the accentuation!) of individual cognitive shortcomings could, in some situations, provide a productive route to collective forms of cognitive and epistemic success. Speaker Biography Dr Paul Smart Paul Smart is a senior research fellow in the Web and Internet Science research group at the University of Southampton in the UK. He is a Fellow of the British Computer Society, a professional member of the Association of Computing Machinery, and a member of the Cognitive Science Society. Paul’s research interests span a number of disciplines, including philosophy, cognitive science, social science, and computer science. His primary area of research interest relates to the social and cognitive implications of Web and Internet technologies. Paul received his bachelors degree in Psychology from the University of Nottingham. He also holds a PhD in Experimental Psychology from the University of Sussex.

Progettazione di un sistema di Location Intelligence per una multiutility

Le informazioni di tipo geografico caratterizzano più dell'80% dei dati utilizzati nei processi decisionali di ogni grande azienda e la loro pervasività è in costante aumento. La Location Intelligence è un insieme di strumenti, metodologie e processi nati con l'obiettivo di analizzare e comprendere a pieno il patrimonio informativo presente in questi dati geolocalizzati. In questo progetto di tesi si è sviluppato un sistema completo di Location Intelligence in grado di eseguire analisi aggregate dei dati georeferenziati prodotti durante l'operatività quotidiana di una grande azienda multiservizi italiana. L’immediatezza dei report grafici e le comparazioni su serie storiche di diverse sorgenti informative integrate generano un valore aggiunto derivante dalle correlazioni individuabili solo grazie a questa nuova dimensione di analisi. In questo documento si illustrano tutte le fasi caratterizzanti del progetto, dalla raccolta dei requisiti utente fino all’implementazione e al rilascio dell’applicativo, concludendo con una sintesi delle potenzialità di analisi generate da questa specifica applicazione e ai suoi successivi sviluppi.

Combinative Aspects of Leadership Style and Emotional Intelligence

Purpose – The purpose of this paper is to examine whether the leader’s emotional intelligence influences the leader’s preferences for different ways of combining leadership behaviors (i.e. combinative aspects of leadership style). Design/methodology/approach – The authors used a hybrid design to collect the data to avoid common-method biases. The authors described a high-stress workplace in a vignette and asked participants to rank four styles of combining a task-oriented leadership (i.e. Pressure) statement and a socio-emotional leadership (i.e. Support) statement. The authors then asked participants to complete a Likert-scale based questionnaire on emotional intelligence. Findings – The authors found that leaders who prefer to provide Support immediately before Pressure have higher levels of emotional intelligence than do leaders who prefer the three other combinative styles. Leaders who prefer to provide Pressure and Support separately (i.e. provide Pressure 30 minutes after Support) have the lowest levels of emotional intelligence. Research limitations/implications – A key implicit assumption in the work is that leaders do not want to evoke negative emotions in followers. The authors did not take into account factors that influence leadership style which participating managers would be likely to encounter on a daily basis such as the relationship with the follower, the follower’s level of performance and work experience, the gender of the leader and the gender of the follower, the hierarchical levels of the leader and follower, and the followers’ preferred combinative style. The nature of the sample and the use of a hypothetical scenario are other limitations of the study. Practical implications – Providing leadership behaviors that are regarded as effective is necessary but not enough because the emotional impact of leadership behaviors appears to also depend on how the behaviors are configured. Originality/value – This is the first study to show that the emotional intelligence of leaders is related to their preferences for the manner in which they combine task and social leadership statements. Furthermore, two-factor theories of leadership propose that the effects of task and social leadership are additive. However, the findings show that the effects are interactive.

Scenari applicativi per Smart Home su piattaforma Home Manager: verso il livello intelligence

Analisi degli scenari applicativi in ambiente Home Manager e progettazione, implementazione e collaudo di alcune delle funzionalità proposte.

La Business Intelligence per il monitoraggio delle vendite: il caso Ducati Motor Holding

“La Business Intelligence per il monitoraggio delle vendite: il caso Ducati Motor Holding”. L’obiettivo di questa tesi è quello di illustrare cos’è la Business Intelligence e di mostrare i cambiamenti verificatisi in Ducati Motor Holding, in seguito alla sua adozione, in termini di realizzazione di report e dashboard per il monitoraggio delle vendite. L’elaborato inizia con una panoramica generale sulla storia e gli utilizzi della Business Intelligence nella quale vengono toccati i principali fondamenti teorici: Data Warehouse, data mining, analisi what-if, rappresentazione multidimensionale dei dati, costruzione del team di BI eccetera. Si proseguirà mediante un focus sui Big Data convogliando l’attenzione sul loro utilizzo e utilità nel settore dell’automotive (inteso nella sua accezione più generica e cioè non solo come mercato delle auto, ma anche delle moto), portando in questo modo ad un naturale collegamento con la realtà Ducati. Si apre così una breve overview sull’azienda descrivendone la storia, la struttura commerciale attraverso la quale vengono gestite le vendite e la gamma dei prodotti. Dal quarto capitolo si entra nel vivo dell’argomento: la Business Intelligence in Ducati. Si inizia descrivendo le fasi che hanno fino ad ora caratterizzato il progetto di Business Analytics (il cui obiettivo è per l'appunto introdurre la BI i azienda) per poi concentrarsi, a livello prima teorico e poi pratico, sul reporting sales e cioè sulla reportistica basata sul monitoraggio delle vendite.

Does Emotional Intelligence have a “Dark” Side? A Review of the Literature

Emotional intelligence (EI) was once touted as the ‘panacea’ for a satisfying and successful life. Consequently, there has been much emphasis on developing interventions to promote this personal resource in applied settings. Despite this, a growing body of research has begun to identify particular contexts when EI does not appear helpful and may even be deleterious to a person, or those they have contact with, suggesting a ‘dark’ side to the construct. This paper provides a review of emergent literature to examine when, why and how trait and ability EI may contribute to negative intrapersonal (psychological ill-health; stress reactivity) and interpersonal outcomes (emotional manipulation; antisocial behaviour). Negative effects were found to operate across multiple contexts (health, academic, occupational) however these were often indirect, suggesting that outcomes depend on pre-existing qualities of the person. Literature also points to the possibility of ‘optimal’ levels of EI – both within and across EI constructs. Uneven profiles of self-perceptions (trait facets) or actual emotional skills contribute to poorer outcomes, particularly emotional awareness and management. Moreover, individuals who possess high levels of skill but have lower self-perceptions of their abilities fare worse that those with more balanced profiles. Future research must now improve methodological and statistical practices to better capture EI in context and the negative corollary associated with high levels.

L'intelligence émotionelle et le leadership

Le titre de l'essai « L'intelligence émotionnelle et le leadership » fait le lien avec le nouveau concept de la connaissance de soi et les relations interpersonnelles. Le récit du cheminement du directeur général, les expériences qu'il a vécues et surtout les caractéristiques de son modèle de gestion, où les relations interpersonnelles et le développement des qualités humaines occupent une place prépondérante, font appel à l'exploitation de nouveaux talents. Le nouveau contexte de travail issu des récents bouleversements des structures scolaires, jumelé au nouveau modèle de gestion imposé par la loi 180, fait ressortir encore plus les besoins des employés au regard des relations, de l’empathie et des communications humaines. Dorénavant, la visibilité de la direction d'école sera beaucoup plus grande, de sorte que ses aptitudes ou ses carences personnelles et relationnelles seront davantage perçues. [...]

Artificial intelligence and criminal evidence: A few topics

Abstract not available

Analysis on the connotation of probability in the artificial intelligence algorithm for economic decision making.

This paper analyzes the inner relations between classical sub-scheme probability and statistic probability, subjective probability and objective probability, prior probability and posterior probability, transition probability and probability of utility, and further analysis the goal, method, and its practical economic purpose which represent by these various probability from the perspective of mathematics, so as to deeply understand there connotation and its relation with economic decision making, thus will pave the route for scientific predication and decision making.

An ecosystem of products and systems for ambient intelligence – the AAL4ALL users perspective

Texto completo em atas de encontros científicos internacionais com arbitragem

Potential of civic crowdfunding to the intelligence of cities and social innovation: an exploratory study

The concepts of smart city and social innovation in combination with the increasing use of ICT by citizens and public authorities could enhance the involvement of people on the decisions that directly affect their daily life. A case study approach was adopted to illustrate the potential of civic crowdfunding for increasing the participation and collaboration between citizens, firms and government. The analysis of two exemplary cases shows that civic crowdfunding platforms could be used by public administration to engage communities in the search of solutions to local problems. Likewise, it could be used to reinforce the community ties and to leverage the bonds among the stakeholders and the partners of the community ecosystem.

Improvement of Virtual Screening Predictions using Computational Intelligence Methods

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to improve accuracy of scoring functions used in most VS methods we propose a hybrid novel approach where neural networks (NNET) and support vector machines (SVM) methods are trained with databases of known active (drugs) and inactive compounds, this information being exploited afterwards to improve VS predictions.