Andrea Aler Tubella
Biographic Data
| ID | 7716846 |
|---|---|
| NAME | Andrea Aler Tubella |
| GIVEN NAMES | Andrea Aler |
| FAMILY NAME | Tubella |
| SIGNATURE | TUBELLA A A |
| AFFILIATIONS | Umeå University |
| ORCID | 0000-0002-8423-8029 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
How to teach responsible AI in Higher Education
In recent years, the European Union has advanced towards responsible and sustainable Artificial Intelligence (AI) research, development and innovation. While the Ethics Guidelines for Trustworthy AI released in 2019 and the AI Act in 2021 set the starting point for a European Ethical AI, there are still several challenges to translate such advances into the public debate, education and practical learning. This paper contributes towards closing th…
Beyond the Binary --- Queering AI for an Inclusive Future
research-article Open Access Share on Beyond the Binary --- Queering AI for an Inclusive Future Authors: Evelina Liliequist Umeå University Umeå UniversityView Profile , Andrea Aler Tubella Umeå University Umeå UniversityView Profile , Karin Danielsson Umeå University Umeå UniversityView Profile , Coppélie Cocq Umeå University Umeå UniversityView Profile Authors Info & Claims InteractionsVolume 30Issue 3May + June 2023pp 31–33https://doi.org/10.1…
Ethical implications of fairness interventions
The importance of fairness in machine learning models is widely acknowledged, and ongoing academic debate revolves around how to determine the appropriate fairness definition, and how to tackle the trade-off between fairness and model performance. In this paper we argue that besides these concerns, there can be ethical implications behind seemingly purely technical choices in fairness interventions in a typical model development pipeline. As an e…
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Ethical implications of fairness interventions
The importance of fairness in machine learning models is widely acknowledged, and ongoing academic debate revolves around how to determine the appropriate fairness definition, and how to tackle the trade-off between fairness and model performance. In this paper we argue that besides these concerns, there can be ethical implications behind seemingly purely technical choices in fairness interventions in a typical model development pipeline. As an e…
Beyond the Binary --- Queering AI for an Inclusive Future
research-article Open Access Share on Beyond the Binary --- Queering AI for an Inclusive Future Authors: Evelina Liliequist Umeå University Umeå UniversityView Profile , Andrea Aler Tubella Umeå University Umeå UniversityView Profile , Karin Danielsson Umeå University Umeå UniversityView Profile , Coppélie Cocq Umeå University Umeå UniversityView Profile Authors Info & Claims InteractionsVolume 30Issue 3May + June 2023pp 31–33https://doi.org/10.1…
How to teach responsible AI in Higher Education
In recent years, the European Union has advanced towards responsible and sustainable Artificial Intelligence (AI) research, development and innovation. While the Ethics Guidelines for Trustworthy AI released in 2019 and the AI Act in 2021 set the starting point for a European Ethical AI, there are still several challenges to translate such advances into the public debate, education and practical learning. This paper contributes towards closing th…
Computer Science (3 works) · Ethics and Social Impacts of AI (3 works) · Economics (2 works) · Explainable Artificial Intelligence (XAI (2 works) · Adversarial Robustness in Machine Learning (1 work) · Artificial Intelligence in Healthcare and Education (1 work) · Business (1 work) · Citation (1 work) · Digital Economy and Work Transformation (1 work) · Engineering (1 work)