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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... -
Fairer machine learning in the real world
Mitigating discrimination without collecting sensitive data Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used... -
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... -
Geo-semantic-parsing AI-powered geoparsing by traversing semantic knowledge g...
Online social networks convey rich information about geospatial facets of reality. However in most cases, geographic information is not explicit and structured, thus... -
Towards better social crisis data with HERMES Hybrid sensing for EmeRgency Ma...
People involved in mass emergencies increasingly publish information-rich contents in Online Social Networks (OSNs), thus acting as a distributed and resilient network of... -
Interaction Strength Analysis to Model Retweet Cascade Graphs
Tracking information diffusion is a non-trivial task and it has been widely studied across different domains and platforms. The advent of social media has led to even more... -
UTLDR: an agent-based framework for modelling infectious diseases and public ...
Nowadays, due to the SARS-CoV-2 pandemic, epidemic modeling is experiencing a constantly growing interest from researchers of heterogeneous fields of study. Indeed, the vast...-
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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... -
An ethico-legal framework for social data science
This paper presents a framework for research infrastructures enabling ethically sensitive and legally compliant data science in Europe. Our goal is to describe how to design... -
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... -
Algorithmic Accountability and Public Reason
The ever-increasing application of algorithms to decision-making in a range of social contexts has prompted demands for algorithmic accountability. Accountable decision-makers... -
A Critical Reassessment of the Saerens-Latinne-Decaestecker Algorithm
We critically re-examine the Saerens-Latinne-Decaestecker (SLD) algorithm, a well-known method for estimating class prior probabilities (“priors”) and adjusting posterior... -
General confidentiality and utility metrics for privacy-preserving data publi...
Anonymization for privacy-preserving data publishing, also known as statistical disclosure control (SDC), can be viewed under the lens of the permutation model. According to... -
Proposal for a Regulation of the European Parliament and the Council laying d...
Our remarks focus on two main issues: 1) providing operational tools to link the ethics and the legal dimension of a Trustworthy AI avoiding risks of ethics washing; 2) the... -
The Role of the GDPR in Designing the European Strategy on Artificial Intelli...
Starting from an analysis of the EU Reg. n. 2016/679 on General Data Protection Regulation (GDPR), the Author deals with the opportunity to translate the current strategies on...-
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