Call for Papers: Topical collection 'Ethics and Information Technology'

Call for Papers for Springers' Topical Collection - Deadline: 15th December 2022

Pubblicato: 01 ottobre 2022

The Culture of Trustworthy AI. Public debate, Education and Practical Learning

 

Over the last years, the European Union has committed towards responsible and sustainable Artificial Intelligence research, development and innovation. In 2019, the High-Level Expert Group on AI (AI HLEG) delivered the Ethics Guidelines for Trustworthy AI and in 2021 the Commission put forward the proposal of a regulatory framework to address different AI risk levels, known as the AI Act. Besides rules and principles, building a Trustworthy AI culture poses several challenges to the whole AI ecosystem, such as:

1) how to create meaningful and constructive debates involving experts with multidisciplinary backgrounds, but also citizens and people who might be directly or indirectly affected by AI systems;

2) the cultural equipment needed to help future AI experts cope with the complexity of societal and ethical changes generated by AI and data-intensive applications;

3) how to translate these cultural resources into working experience with a view to creating a mutual and beneficial interaction between the theory and the practice of Trustworthy AI.

This topical collection aims to explore how we can get closer to a Trustworthy AI Culture sharing investigations and good practices moving along the trajectories suggested by the AI HLEG guidelines: public debate, education and practical learning. This topical collection calls for research papers, project reports, or position papers addressing, but not limited to the following topics:

- Experiences of multidisciplinary perspectives and methodologies that contribute to building a Trustworthy AI culture;

- Critical and constructive analysis of ideas and strategies aimed at building an ecosystem of trust;

- Contributions to the identification of disciplinary gaps (conceptual, language, skills and social diversity) and how to address them;

- Analysis of methodologies or approaches that can help AI experts address tensions and trade-offs among ethical principles in play;

- Approaches to the definition of educational strategies, content and skills to be included in courses dealing with Trustworthy AI;

- Approaches that can contribute to a better integration of the humanities into AI research and development;

- Methods to apply Trustworthy AI concepts and requirements into practice and processes to validate and verify them;

- Proposals of participatory methods that involve all stakeholders of the AI system life-cycle, including the developers, researchers, policy-makers, governments, private and public sectors and the society.

More: https://link.springer.com/collections/bheicacbbd