Bias in data-driven artificial intelligence systems—An introductory survey

Artificial Intelligence (AI)-based systems are widely employed nowadays to make decisions that have far-reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing concerns about potential human rights issues. Therefore, it is necessary to move beyond traditional AI algorithms optimized for predictive performance and embed ethical and legal principles in their design, training, and deployment to ensure social good while still benefiting from the huge potential of the AI technology. The goal of this survey is to provide a broad multidisciplinary overview of the area of bias in AI systems, focusing on technical challenges and solutions as well as to suggest new research directions towards approaches well-grounded in a legal frame. In this survey, we focus on data-driven AI, as a large part of AI is powered nowadays by (big) data and powerful machine learning algorithms. If otherwise not specified, we use the general term bias to describe problems related to the gathering or processing of data that might result in prejudiced decisions on the bases of demographic features such as race, sex, and so forth. This article is categorized under: Commercial, Legal, and Ethical Issues > Fairness in Data Mining Commercial, Legal, and Ethical Issues > Ethical Considerations Commercial, Legal, and Ethical Issues > Legal Issues

Bias in data-driven artificial intelligence systems - An introductory survey

Artificial Intelligence (AI)-based systems are widely employed nowadays to make decisions that have far-reaching impact on individuals and society. Their decisions might affect everyone, everywhere, and anytime, entailing concerns about potential human rights issues. Therefore, it is necessary to move beyond traditional AI algorithms optimized for predictive performance and embed ethical and legal principles in their design, training, and deployment to ensure social good while still benefiting from the huge potential of the AI technology. The goal of this survey is to provide a broad multidisciplinary overview of the area of bias in AI systems, focusing on technical challenges and solutions as well as to suggest new research directions towards approaches well-grounded in a legal frame. In this survey, we focus on data-driven AI, as a large part of AI is powered nowadays by (big) data and powerful machine learning algorithms. If otherwise not specified, we use the general term bias to describe problems related to the gathering or processing of data that might result in prejudiced decisions on the bases of demographic features such as race, sex, and so forth. This article is categorized under: Commercial, Legal, and Ethical Issues > Fairness in Data Mining Commercial, Legal, and Ethical Issues > Ethical Considerations Commercial, Legal, and Ethical Issues > Legal Issues

Recording the trace of visual search: a research method of the selectivity of hole as a basic shape characteristic

158 σ.Η παρούσα διπλωματική εργασία πραγματοποιήθηκε με σκοπό την μελέτη και τη διερεύνηση του χαρτογραφούμενου οπτικού ίχνους που δημιουργείται κατά τη διάρκεια της αναζήτησης στόχων πάνω σε μια οπτική σκηνή. Για την διεξαγωγή της έρευνας, σχεδιάστηκε ένα χαρτογραφικό πείραμα, το οποίο χρησιμοποιεί τα υπόβαθρα και τα σύμβολα ενός προηγούμενου χαρτογραφικού πειράματος του εργαστηρίου Χαρτογραφίας. Τα σύμβολα που διαδραματίζουν το ρόλο των στόχων χαρακτηρίζονται από την τοπολογική ιδιότητα της οπής, η οποία τα κάνει μοναδικά σε σχέση με τους συμπαγής περισπαστές. Ο παράγοντας της επιλεκτικότητας της συγκεκριμένης ιδιότητας του σχήματος εξετάζεται τόσο στην περίπτωση των γεωμετρικών όσο και στην αντίστοιχη των εικονογραφικών συμβόλων. Η μεθοδολογία καταγραφής των οφθαλμικών κινήσεων συνδυάζεται με τις κλασσικές μεθόδους διεξαγωγής ομοειδών πειραμάτων, δίνοντας μια νέα μορφή αποτελεσμάτων, η οποία παρέχει ένα εμπλουτισμένο σύνολο πληροφοριών για την διαδικασία της οπτικής αναζήτησης.The aim of the present diploma thesis is the study of the visual trace, which is generated during the search on targets on a visual scene. For the performance of the research, a cartographic experiment was designed, which uses the base map and the symbols of a previous cartographic experiment done in the laboratory of Cartography. The symbols that play the role of targets have a hole as a topological property, which makes them unique compare to the compact distractors. The factor of selectivity of this property of shape is examined both in the case of geometric and pictorial symbols. The methodology of eye movements recording combined with traditional methods of similar experiments, is giving a new type of results, providing an enriched set of information on the process of visual search.Βασίλειος Ε. Κρασανάκη

Understanding fatherhood in Greece: father's involvement in child care

The present study aims to depict a picture of Greek fathers concerning their involvement in family and child-centered tasks over the first year of the child. Eighty fathers from rural areas with low educational and occupational status and eighty fathers from urban districts with high educational and occupational status were asked to talk about their own perceptions of fatherhood and also their participation into two parenting commitments: (a) preparations before and after the birth of the child and (b) involvement in play with the child and a variety of daily child-care tasks. The results show that fathers in urban regions were more involved in these activities than their counterparts in rural areas. All fathers valued fatherhood as a pleasant experience. Many fathers, however, stated that child-rearing responsibilities cause them a lot of psychological strain. The results are discussed in relation to the division of roles between spouses in Greek families