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Origin and destination attachment: study of cultural integration on Twitter
The cultural integration of immigrants conditions their overall socio-economic integration as well as natives’ attitudes towards globalisation in general and immigration in...-
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Human migration the big data perspective
How can big data help to understand the migration phenomenon? In this paper, we try to answer this question through an analysis of various phases of migration, comparing...-
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Algorithmic Decision Making Based on ML from Big Data. Can Transparency Resto...
Decision-making assisted by algorithms developed by machine learning is increasingly determining our lives. Unfortunately, full opacity about the process is the norm. Would... -
Machine Learning Explainability Via Microaggregation and Shallow Decision Trees
Artificial intelligence (AI) is being deployed in missions that are increasingly critical for human life. To build trust in AI and avoid an algorithm-based authoritarian... -
Fair Transparent and Accountable Algorithmic Decision making Processes
The Premise, the Proposed Solutions, and the Open Challenges The combination of increased availability of large amounts of fine-grained human behavioral data and advances in... -
Volleyball-Specific Skills and Cognitive Functions Can Discriminate Players o...
Formenti, D, Trecroci, A, Duca, M, Vanoni, M, Ciovati, M, Rossi, A, and Alberti, G. Volleyball-specific skills and cognitive functions can discriminate players of different...-
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Interpretable socioeconomic status inference from aerial imagery through urba...
Urbanization is a great challenge for modern societies, promising better access to economic opportunities, but widening socioeconomic inequalities. Accurately tracking this...-
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Evaluating local explanation methods on ground truth
Evaluating local explanation methods is a difficult task due to the lack of a shared and universally accepted definition of explanation. In the literature, one of the most...-
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Explanation in artificial intelligence. Insights from the social sciences
There has been a recent resurgence in the area of explainable artificial intelligence as researchers and practitioners seek to provide more transparency to their algorithms.... -
Grounds for Trust. Essential Epistemic Opacity and Computational Reliabilism
Several philosophical issues in connection with computer simulations rely on the assumption that results of simulations are trustworthy. Examples of these include the debate... -
Fair Prediction with Disparate Impact A Study of Bias in Recidivism Predictio...
Recidivism prediction instruments (RPIs) provide decision-makers with an assessment of the likelihood that a criminal defendant will reoffend at a future point in time.... -
Solving the Black Box Problem. A Normative Framework for Explainable Artifici...
Many of the computing systems programmed using Machine Learning are opaque: it is difficult to know why they do what they do or how they work. Explainable Artificial... -
Toward Accountable Discrimination Aware Data Mining
"Big Data" and data-mined inferences are affecting more and more of our lives, and concerns about their possible discriminatory effects are growing. Methods for... -
Algorithmic Decision Making Based on Machine Learning from Big Data
Decision-making assisted by algorithms developed by machine learning is increasingly determining our lives. Unfortunately, full opacity about the process is the norm. Would... -
A decade of social bot detection
Bots increasingly tamper with political elections and economic discussions. Tracing trends in detection strategies and key suggestions on how to win the fight.-
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How the machine thinks. Understanding opacity in machine learning algorithms
This article considers the issue of opacity as a problem for socially consequential mechanisms of classification and ranking, such as spam filters, credit card fraud... -
Seeing without knowing. Limitations of transparency and its application to al...
Models for understanding and holding systems accountable have long rested upon ideals and logics of transparency. Being able to see a system is sometimes equated with being able... -
Bias in algorithmic filtering and personalization
Online information intermediaries such as Facebook and Google are slowly replacing traditional media channels thereby partly becoming the gatekeepers of our society. To deal... -
AI and Big Data A blueprint for a human rights and social and ethical impact ...
Building on studies of the collective dimension of data protection, this article sets out to embed this new perspective in an assessment model centred on human rights (Human... -
Accountability for the Use of Algorithms in a Big Data Environment
Accountability is the ability to provide good reasons in order to explain and to justify actions, decisions, and policies for a (hypothetical) forum of persons or...
