-
The democracy of emergency at the time of the coronavirus the virtues of privacy
The emergency of the Coronavirus imposes a cultural debate on the balancing of rights, freedoms and social responsibilities, finalized to the protection of individual and... -
Recommender systems and their ethical challenges
This article presents the first, systematic analysis of the ethical challenges posed by recommender systems through a literature review. The article identifies six areas of... -
Privacy in the clouds
Informational self-determination refers to the right or ability of individuals to exercise personal control over the collection, use and disclosure of their personal data by... -
Measuring discrimination in algorithmic decision making
Society is increasingly relying on data-driven predictive models for automated decision making. This is not by design, but due to the nature and noisiness of observational... -
Explaining misclassification and attacks in deep learning via random forests
Artificial intelligence, and machine learning (ML) in particular, is being used for different purposes that are critical for human life. To avoid an algorithm-based...-
PDF
The resource: 'Link to Publication' is not accessible as guest user. You must login to access it!
-
PDF
-
Identifying and exploiting homogeneous communities in labeled networks
Attribute-aware community discovery aims to find well-connected communities that are also homogeneous w.r.t. the labels carried by the nodes. In this work, we address such a... -
Ethical Value Centric Cybersecurity. A Methodology Based on a Value Graph
Our society is being shaped in a non-negligible way by the technological advances of recent years, especially in information and communications technologies (ICTs). The... -
Efficient detection of Byzantine attacks in federated learning using last lay...
Federated learning (FL) is an alternative to centralized machine learning (ML) that builds a model across multiple decentralized edge devices (a.k.a. workers) that own the...-
PDF
The resource: 'Link to Publication' is not accessible as guest user. You must login to access it!
-
PDF
-
Fairness and Abstraction in Sociotechnical Systems
A key goal of the fair-ML community is to develop machine-learning based systems that, once introduced into a social context, can achieve social and legal outcomes such as... -
Fair detection of poisoning attacks in federated learning
Federated learning is a decentralized machine learning technique that aggregates partial models trained by a set of clients on their own private data to obtain a global model....-
PDF
The resource: 'Link to Publication' is not accessible as guest user. You must login to access it!
-
PDF
-
Conformity a Path-Aware Homophily measure for Node-Attributed Networks
Unveil the homophilic/heterophilic behaviors that characterize the wiring patterns of complex networks is an important task in social network analysis, often approached...-
PDF
The resource: 'Link to Publication' is not accessible as guest user. You must login to access it!
-
PDF
-
Designing for human rights in AI
In the age of Big Data, companies and governments are increasingly using algorithms to inform hiring decisions, employee management, policing, credit scoring, insurance... -
Democratizing Algorithmic Fairness
Machine learning algorithms can now identify patterns and correlations in (big) datasets and predict outcomes based on the identified patterns and correlations. They can then... -
Big Data Ethics
The speed of development in Big Data and associated phenomena, such as social media, has surpassed the capacity of the average consumer to understand his or her actions and...
